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natural logic

Толкование Перевод

1 natural logic

мат. естественная логика

Большой англо-русский и русско-английский словарь > natural logic
2 natural logic

1) Математика: естественная логика

2) Лингвистика: наивная логика, практическая логика

Универсальный англо-русский словарь > natural logic
3 natural logic

мат.

естественная логика

English-Russian scientific dictionary > natural logic
4 natural logic

естественная логика

Англо-русский словарь по исследованиям и ноу-хау > natural logic
5 logic

1) логика || логический

2) вчт логические схемы, логика

3) логический блок; логический узел

•

logic with identity — логика с тождеством

logic without identity — логика без тождества

- algebraic logic

- applied logic

- auxiliary logic

- bivalent logic

- cellular logic

- class logic

- classical logic

- classical propositional logic

- commodity logic

- continuous logic

- countably complete logic

- decision logic

- decoding logic

- deductive logic

- derivative logic

- deterministic logic

- dialectical logic

- digitizing logic

- dual logic

- dyadic logic

- dynamic logic

- elementary logic

- empirical logic

- equational logic

- extended logic

- extensional logic

- external logic

- feature logic

- finite-valued logic

- first-order logic

- free logic

- fuzzy logic

- general modal logic

- generalized logic

- generalized stochastic logic

- heuristic logic

- imperative logic

- implicational logic

- inductive logic

- inductively generated logic

- infinitary logic

- infinite-valued logic

- intensional logic

- intermediate logic

- intrinsic logic

- intuitionistic logic

- iterative logic

- lattice-theoretic logic

- limit logic

- logic of certainty

- logic of evidence

- logic of existence

- logic of higher order

- logic of modalities

- logic of norms

- logic of part

- logic of preference

- logic of strict implication

- logic of truth

- logic of verification

- logic of whole

- minimal logic

- modal logic

- monadic logic

- multivalued logic

- natural logic

- nonclassical logic

- nonconstructive logic

- nonmonotonic logic

- normative logic

- n-valued logic

- object logic

- orthodox logic

- polyvalent logic

- positive logic

- predicate logic

- projectively generated logic

- propositional logic

- pure logic

- quantificational logic

- quite full logic

- reduced logic

- redundant logic

- search logic

- semicomplete logic

- sentential logic

- separable logic

- set-theoretic predicate logic

- shielded

- situational logic

- static logic

- stochastic logic

- strict logic

- strongly strict logic

- superintuitionistic logic

- switching logic

- syllogistic logic

- system logic

- technical logic

- tense logic

- three-level logic

- three-valued logic

- topological logic

- traditional logic

- transforming logic

- trivalent logic

- unordered logic

- unorthodox logic

- unspecialized logic

English-Russian scientific dictionary > logic
6 Logic

   1) The Science of Logic Finds Ordinary Language to Be an Obstacle

   My initial step... was to attempt to reduce the concept of ordering in a sequence to that of logical consequence, so as to proceed from there to the concept of number. To prevent anything intuitive from penetrating here unnoticed, I had to bend every effort to keep the chain of inference free of gaps. In attempting to comply with this requirement in the strictest possible way, I found the inadequacy of language to be an obstacle. (Frege, 1972, p. 104)

   2) Logic Is a Microscope

   I believe I can make the relation of my 'conceptual notation' to ordinary language clearest if I compare it to the relation of the microscope to the eye. The latter, because of the range of its applicability and because of the ease with which it can adapt itself to the most varied circumstances, has a great superiority over the microscope. Of course, viewed as an optical instrument it reveals many imperfections, which usually remain unnoticed only because of its intimate connection with mental life. But as soon as scientific purposes place strong requirements upon sharpness of resolution, the eye proves to be inadequate.... Similarly, this 'conceptual notation' is devised for particular scientific purposes; and therefore one may not condemn it because it is useless for other purposes. (Frege, 1972, pp. 104-105)

   3) Logic Carries on an Unceasing Struggle with Psychology

   To sum up brieﬂy, it is the business of the logician to conduct an unceasing struggle against psychology and those parts of language and grammar which fail to give untrammeled expression to what is logical. He does not have to answer the question: How does thinking normally take place in human beings? What course does it naturally follow in the human mind? What is natural to one person may well be unnatural to another. (Frege, 1979, pp. 6-7)

   4) Logic Should Replace the Ordinary Language of Everyday Discourse

   We are very dependent on external aids in our thinking, and there is no doubt that the language of everyday life-so far, at least, as a certain area of discourse is concerned-had first to be replaced by a more sophisticated instrument, before certain distinctions could be noticed. But so far the academic world has, for the most part, disdained to master this instrument. (Frege, 1979, pp. 6-7)

   5) Logic Is Unnatural

   There is no reproach the logician need fear less than the reproach that his way of formulating things is unnatural.... If we were to heed those who object that logic is unnatural, we would run the risk of becoming embroiled in interminable disputes about what is natural, disputes which are quite incapable of being resolved within the province of logic. (Frege, 1979, p. 128)

   6) The Significance of " Baby Logic" for Linguistics

   [L]inguists will be forced, internally as it were, to come to grips with the results of modern logic. Indeed, this is apparently already happening to some extent. By "logic" is not meant here recursive function-theory, California model-theory, constructive proof-theory, or even axiomatic settheory. Such areas may or may not be useful for linguistics. Rather under "logic" are included our good old friends, the homely locutions "and," "or," "if-then," "if and only if," "not," "for all x," "for some x," and "is identical with," plus the calculus of individuals, event-logic, syntax, denotational semantics, and... various parts of pragmatics.... It is to these that the linguist can most profitably turn for help. These are his tools. And they are "clean tools," to borrow a phrase of the late J. L. Austin in another context, in fact, the only really clean ones we have, so that we might as well use them as much as we can. But they constitute only what may be called "baby logic." Baby logic is to the linguist what "baby mathematics" (in the phrase of Murray Gell-Mann) is to the theoretical physicist-very elementary but indispensable domains of theory in both cases. (Martin, 1969, pp. 261-262)

   7) The Existence of a Mental Logic Denied

   There appears to be no branch of deductive inference that requires us to assume the existence of a mental logic in order to do justice to the psychological phenomena. To be logical, an individual requires, not formal rules of inference, but a tacit knowledge of the fundamental semantic principle governing any inference; a deduction is valid provided that there is no way of interpreting the premises correctly that is inconsistent with the conclusion. Logic provides a systematic method for searching for such counter-examples. The empirical evidence suggests that ordinary individuals possess no such methods. (Johnson-Laird, quoted in Mehler, Walker & Garrett, 1982, p. 130)

   8) The Fundamental Paradox of Logic

   The fundamental paradox of logic [that "there is no class (as a totality) of those classes which, each taken as a totality, do not belong to themselves" (Russell to Frege, 16 June 1902, in van Heijenoort, 1967, p. 125)] is with us still, bequeathed by Russell-by way of philosophy, mathematics, and even computer science-to the whole of twentieth-century thought. Twentieth-century philosophy would begin not with a foundation for logic, as Russell had hoped in 1900, but with the discovery in 1901 that no such foundation can be laid. (Everdell, 1997, p. 184)

Historical dictionary of quotations in cognitive science > Logic
7 natural language logic

Лингвистика: естественноязыковая логика, логика естественного языка

Универсальный англо-русский словарь > natural language logic
8 body natural defence system

иммунная система

fire-protection system — противопожарная система

fixed-feature nc system — аппаратная система ЧПУ

flexible nc system — программируемая система ЧПУ

fluid logic system — струйная логическая система

fuel metering system — топливодозирующая система

English-Russian big medical dictionary > body natural defence system
9 естественная логика

мат. natural logic

Большой англо-русский и русско-английский словарь > естественная логика
10 Artificial Intelligence

   1) Programs and the Complexity of Human Mental Processes

   In my opinion, none of [these programs] does even remote justice to the complexity of human mental processes. Unlike men, "artificially intelligent" programs tend to be single minded, undistractable, and unemotional. (Neisser, 1967, p. 9)

   2) Artificial Intelligence Is an Engineering Discipline

   Future progress in [artificial intelligence] will depend on the development of both practical and theoretical knowledge.... As regards theoretical knowledge, some have sought a unified theory of artificial intelligence. My view is that artificial intelligence is (or soon will be) an engineering discipline since its primary goal is to build things. (Nilsson, 1971, pp. vii-viii)

   3) A Sceptical View of Artificial Intelligence

   Most workers in AI [artificial intelligence] research and in related fields confess to a pronounced feeling of disappointment in what has been achieved in the last 25 years. Workers entered the field around 1950, and even around 1960, with high hopes that are very far from being realized in 1972. In no part of the field have the discoveries made so far produced the major impact that was then promised.... In the meantime, claims and predictions regarding the potential results of AI research had been publicized which went even farther than the expectations of the majority of workers in the field, whose embarrassments have been added to by the lamentable failure of such inﬂated predictions....

   When able and respected scientists write in letters to the present author that AI, the major goal of computing science, represents "another step in the general process of evolution"; that possibilities in the 1980s include an all-purpose intelligence on a human-scale knowledge base; that awe-inspiring possibilities suggest themselves based on machine intelligence exceeding human intelligence by the year 2000 [one has the right to be skeptical]. (Lighthill, 1972, p. 17)

   4) Just as Astronomy Succeeded Astrology, the Discovery of Intellectual Processes in Machines Should Lead to a Science, Eventually

   Just as astronomy succeeded astrology, following Kepler's discovery of planetary regularities, the discoveries of these many principles in empirical explorations on intellectual processes in machines should lead to a science, eventually. (Minsky & Papert, 1973, p. 11)

   5) Problems in Machine Intelligence Arise Because Things Obvious to Any Person Are Not Represented in the Program

   Many problems arise in experiments on machine intelligence because things obvious to any person are not represented in any program. One can pull with a string, but one cannot push with one.... Simple facts like these caused serious problems when Charniak attempted to extend Bobrow's "Student" program to more realistic applications, and they have not been faced up to until now. (Minsky & Papert, 1973, p. 77)

   6) The Meaning of a Symbolic Description

   What do we mean by [a symbolic] "description"? We do not mean to suggest that our descriptions must be made of strings of ordinary language words (although they might be). The simplest kind of description is a structure in which some features of a situation are represented by single ("primitive") symbols, and relations between those features are represented by other symbols-or by other features of the way the description is put together. (Minsky & Papert, 1973, p. 11)

   7) The Principle of Artificial Intelligence

   [AI is] the use of computer programs and programming techniques to cast light on the principles of intelligence in general and human thought in particular. (Boden, 1977, p. 5)

   8) Artificial Intelligence Recognizes the Need for Knowledge in Its Systems

   The word you look for and hardly ever see in the early AI literature is the word knowledge. They didn't believe you have to know anything, you could always rework it all.... In fact 1967 is the turning point in my mind when there was enough feeling that the old ideas of general principles had to go.... I came up with an argument for what I called the primacy of expertise, and at the time I called the other guys the generalists. (Moses, quoted in McCorduck, 1979, pp. 228-229)

   9) Artificial Intelligence Is Psychology in a Particularly Pure and Abstract Form

   The basic idea of cognitive science is that intelligent beings are semantic engines-in other words, automatic formal systems with interpretations under which they consistently make sense. We can now see why this includes psychology and artificial intelligence on a more or less equal footing: people and intelligent computers (if and when there are any) turn out to be merely different manifestations of the same underlying phenomenon. Moreover, with universal hardware, any semantic engine can in principle be formally imitated by a computer if only the right program can be found. And that will guarantee semantic imitation as well, since (given the appropriate formal behavior) the semantics is "taking care of itself" anyway. Thus we also see why, from this perspective, artificial intelligence can be regarded as psychology in a particularly pure and abstract form. The same fundamental structures are under investigation, but in AI, all the relevant parameters are under direct experimental control (in the programming), without any messy physiology or ethics to get in the way. (Haugeland, 1981b, p. 31)

    10) There Are Many Types of Reasoning

   There are many different kinds of reasoning one might imagine:

    Formal reasoning involves the syntactic manipulation of data structures to deduce new ones following prespecified rules of inference. Mathematical logic is the archetypical formal representation. Procedural reasoning uses simulation to answer questions and solve problems. When we use a program to answer What is the sum of 3 and 4? it uses, or "runs," a procedural model of arithmetic. Reasoning by analogy seems to be a very natural mode of thought for humans but, so far, difficult to accomplish in AI programs. The idea is that when you ask the question Can robins ﬂy? the system might reason that "robins are like sparrows, and I know that sparrows can ﬂy, so robins probably can ﬂy."

    Generalization and abstraction are also natural reasoning process for humans that are difficult to pin down well enough to implement in a program. If one knows that Robins have wings, that Sparrows have wings, and that Blue jays have wings, eventually one will believe that All birds have wings. This capability may be at the core of most human learning, but it has not yet become a useful technique in AI.... Meta- level reasoning is demonstrated by the way one answers the question What is Paul Newman's telephone number? You might reason that "if I knew Paul Newman's number, I would know that I knew it, because it is a notable fact." This involves using "knowledge about what you know," in particular, about the extent of your knowledge and about the importance of certain facts. Recent research in psychology and AI indicates that meta-level reasoning may play a central role in human cognitive processing. (Barr & Feigenbaum, 1981, pp. 146-147)

    11) Programs Are Beginning to Do Things That Critics Have Asserted to Be Impossible

   Suffice it to say that programs already exist that can do things-or, at the very least, appear to be beginning to do things-which ill-informed critics have asserted a priori to be impossible. Examples include: perceiving in a holistic as opposed to an atomistic way; using language creatively; translating sensibly from one language to another by way of a language-neutral semantic representation; planning acts in a broad and sketchy fashion, the details being decided only in execution; distinguishing between different species of emotional reaction according to the psychological context of the subject. (Boden, 1981, p. 33)

    12) The Synthesis of Man and Machine

   Can the synthesis of Man and Machine ever be stable, or will the purely organic component become such a hindrance that it has to be discarded? If this eventually happens-and I have... good reasons for thinking that it must-we have nothing to regret and certainly nothing to fear. (Clarke, 1984, p. 243)

    13) The Thesis of Good Old-Fashioned Artificial Intelligence (GOFAI)

   The thesis of GOFAI... is not that the processes underlying intelligence can be described symbolically... but that they are symbolic. (Haugeland, 1985, p. 113)

    14) Artificial Intelligence Provides a Useful Approach to Psychological and Psychiatric Theory Formation

   It is all very well formulating psychological and psychiatric theories verbally but, when using natural language (even technical jargon), it is difficult to recognise when a theory is complete; oversights are all too easily made, gaps too readily left. This is a point which is generally recognised to be true and it is for precisely this reason that the behavioural sciences attempt to follow the natural sciences in using "classical" mathematics as a more rigorous descriptive language. However, it is an unfortunate fact that, with a few notable exceptions, there has been a marked lack of success in this application. It is my belief that a different approach-a different mathematics-is needed, and that AI provides just this approach. (Hand, quoted in Hand, 1985, pp. 6-7)

    15) Four Kinds of Artificial Intelligence

   We might distinguish among four kinds of AI.

   ♦ Nonpsychological AI

   Research of this kind involves building and programming computers to perform tasks which, to paraphrase Marvin Minsky, would require intelligence if they were done by us. Researchers in nonpsychological AI make no claims whatsoever about the psychological realism of their programs or the devices they build, that is, about whether or not computers perform tasks as humans do.

   ♦ Weak Psychological AI

   Research here is guided by the view that the computer is a useful tool in the study of mind. In particular, we can write computer programs or build devices that simulate alleged psychological processes in humans and then test our predictions about how the alleged processes work. We can weave these programs and devices together with other programs and devices that simulate different alleged mental processes and thereby test the degree to which the AI system as a whole simulates human mentality. According to weak psychological AI, working with computer models is a way of refining and testing hypotheses about processes that are allegedly realized in human minds.

   ♦ Strong Psychological AI

... According to this view, our minds are computers and therefore can be duplicated by other computers. Sherry Turkle writes that the "real ambition is of mythic proportions, making a general purpose intelligence, a mind." (Turkle, 1984, p. 240) The authors of a major text announce that "the ultimate goal of AI research is to build a person or, more humbly, an animal." (Charniak & McDermott, 1985, p. 7)

   ♦ Suprapsychological AI

   Research in this field, like strong psychological AI, takes seriously the functionalist view that mentality can be realized in many different types of physical devices. Suprapsychological AI, however, accuses strong psychological AI of being chauvinisticof being only interested in human intelligence! Suprapsychological AI claims to be interested in all the conceivable ways intelligence can be realized. (Flanagan, 1991, pp. 241-242)

    16) Determination of Relevance of Rules in Particular Contexts

   Even if the [rules] were stored in a context-free form the computer still couldn't use them. To do that the computer requires rules enabling it to draw on just those [ rules] which are relevant in each particular context. Determination of relevance will have to be based on further facts and rules, but the question will again arise as to which facts and rules are relevant for making each particular determination. One could always invoke further facts and rules to answer this question, but of course these must be only the relevant ones. And so it goes. It seems that AI workers will never be able to get started here unless they can settle the problem of relevance beforehand by cataloguing types of context and listing just those facts which are relevant in each. (Dreyfus & Dreyfus, 1986, p. 80)

    17) Form and Content Are Not Fundamentally Different

   Perhaps the single most important idea to artificial intelligence is that there is no fundamental difference between form and content, that meaning can be captured in a set of symbols such as a semantic net. (G. Johnson, 1986, p. 250)

    18) The Assumption That the Mind Is a Formal System

   Artificial intelligence is based on the assumption that the mind can be described as some kind of formal system manipulating symbols that stand for things in the world. Thus it doesn't matter what the brain is made of, or what it uses for tokens in the great game of thinking. Using an equivalent set of tokens and rules, we can do thinking with a digital computer, just as we can play chess using cups, salt and pepper shakers, knives, forks, and spoons. Using the right software, one system (the mind) can be mapped into the other (the computer). (G. Johnson, 1986, p. 250)

    19) A Statement of the Primary and Secondary Purposes of Artificial Intelligence

   The primary goal of Artificial Intelligence is to make machines smarter.

   The secondary goals of Artificial Intelligence are to understand what intelligence is (the Nobel laureate purpose) and to make machines more useful (the entrepreneurial purpose). (Winston, 1987, p. 1)

    20) Mathematical Logic Provides the Basis for Theory in AI

   The theoretical ideas of older branches of engineering are captured in the language of mathematics. We contend that mathematical logic provides the basis for theory in AI. Although many computer scientists already count logic as fundamental to computer science in general, we put forward an even stronger form of the logic-is-important argument....

   AI deals mainly with the problem of representing and using declarative (as opposed to procedural) knowledge. Declarative knowledge is the kind that is expressed as sentences, and AI needs a language in which to state these sentences. Because the languages in which this knowledge usually is originally captured (natural languages such as English) are not suitable for computer representations, some other language with the appropriate properties must be used. It turns out, we think, that the appropriate properties include at least those that have been uppermost in the minds of logicians in their development of logical languages such as the predicate calculus. Thus, we think that any language for expressing knowledge in AI systems must be at least as expressive as the first-order predicate calculus. (Genesereth & Nilsson, 1987, p. viii)

    21) Perceptual Structures Can Be Represented as Lists of Elementary Propositions

   In artificial intelligence studies, perceptual structures are represented as assemblages of description lists, the elementary components of which are propositions asserting that certain relations hold among elements. (Chase & Simon, 1988, p. 490)

    22) Definitions of Artificial Intelligence

   Artificial intelligence (AI) is sometimes defined as the study of how to build and/or program computers to enable them to do the sorts of things that minds can do. Some of these things are commonly regarded as requiring intelligence: offering a medical diagnosis and/or prescription, giving legal or scientific advice, proving theorems in logic or mathematics. Others are not, because they can be done by all normal adults irrespective of educational background (and sometimes by non-human animals too), and typically involve no conscious control: seeing things in sunlight and shadows, finding a path through cluttered terrain, fitting pegs into holes, speaking one's own native tongue, and using one's common sense. Because it covers AI research dealing with both these classes of mental capacity, this definition is preferable to one describing AI as making computers do "things that would require intelligence if done by people." However, it presupposes that computers could do what minds can do, that they might really diagnose, advise, infer, and understand. One could avoid this problematic assumption (and also side-step questions about whether computers do things in the same way as we do) by defining AI instead as "the development of computers whose observable performance has features which in humans we would attribute to mental processes." This bland characterization would be acceptable to some AI workers, especially amongst those focusing on the production of technological tools for commercial purposes. But many others would favour a more controversial definition, seeing AI as the science of intelligence in general-or, more accurately, as the intellectual core of cognitive science. As such, its goal is to provide a systematic theory that can explain (and perhaps enable us to replicate) both the general categories of intentionality and the diverse psychological capacities grounded in them. (Boden, 1990b, pp. 1-2)

    23) The Computer Can Not Be a Model of the Mind

   Because the ability to store data somewhat corresponds to what we call memory in human beings, and because the ability to follow logical procedures somewhat corresponds to what we call reasoning in human beings, many members of the cult have concluded that what computers do somewhat corresponds to what we call thinking. It is no great difficulty to persuade the general public of that conclusion since computers process data very fast in small spaces well below the level of visibility; they do not look like other machines when they are at work. They seem to be running along as smoothly and silently as the brain does when it remembers and reasons and thinks. On the other hand, those who design and build computers know exactly how the machines are working down in the hidden depths of their semiconductors. Computers can be taken apart, scrutinized, and put back together. Their activities can be tracked, analyzed, measured, and thus clearly understood-which is far from possible with the brain. This gives rise to the tempting assumption on the part of the builders and designers that computers can tell us something about brains, indeed, that the computer can serve as a model of the mind, which then comes to be seen as some manner of information processing machine, and possibly not as good at the job as the machine. (Roszak, 1994, pp. xiv-xv)

    24) Computers Will Not Always Be Inferior to Human Brains

   The inner workings of the human mind are far more intricate than the most complicated systems of modern technology. Researchers in the field of artificial intelligence have been attempting to develop programs that will enable computers to display intelligent behavior. Although this field has been an active one for more than thirty-five years and has had many notable successes, AI researchers still do not know how to create a program that matches human intelligence. No existing program can recall facts, solve problems, reason, learn, and process language with human facility. This lack of success has occurred not because computers are inferior to human brains but rather because we do not yet know in sufficient detail how intelligence is organized in the brain. (Anderson, 1995, p. 2)

Historical dictionary of quotations in cognitive science > Artificial Intelligence
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Historical dictionary of quotations in cognitive science > Bibliography
12 Memory

   1) A Unitary Search Process for All the Phenomena of Memory

   To what extent can we lump together what goes on when you try to recall: (1) your name; (2) how you kick a football; and (3) the present location of your car keys? If we use introspective evidence as a guide, the first seems an immediate automatic response. The second may require constructive internal replay prior to our being able to produce a verbal description. The third... quite likely involves complex operational responses under the control of some general strategy system. Is any unitary search process, with a single set of characteristics and inputoutput relations, likely to cover all these cases? (Reitman, 1970, p. 485)

   2) Semantic Memory Is a Mental Thesaurus

   [Semantic memory] Is a mental thesaurus, organized knowledge a person possesses about words and other verbal symbols, their meanings and referents, about relations among them, and about rules, formulas, and algorithms for the manipulation of these symbols, concepts, and relations. Semantic memory does not register perceptible properties of inputs, but rather cognitive referents of input signals. (Tulving, 1972, p. 386)

   3) The Development of Mnemonic Codes

   The mnemonic code, far from being fixed and unchangeable, is structured and restructured along with general development. Such a restructuring of the code takes place in close dependence on the schemes of intelligence. The clearest indication of this is the observation of different types of memory organisation in accordance with the age level of a child so that a longer interval of retention without any new presentation, far from causing a deterioration of memory, may actually improve it. (Piaget & Inhelder, 1973, p. 36)

   4) The Logic of Some Memory Theorization Is of Dubious Worth in the History of Psychology

   If a cue was effective in memory retrieval, then one could infer it was encoded; if a cue was not effective, then it was not encoded. The logic of this theorization is "heads I win, tails you lose" and is of dubious worth in the history of psychology. We might ask how long scientists will puzzle over questions with no answers. (Solso, 1974, p. 28)

   5) The Constituent Elements of Memory Theory

   We have iconic, echoic, active, working, acoustic, articulatory, primary, secondary, episodic, semantic, short-term, intermediate-term, and longterm memories, and these memories contain tags, traces, images, attributes, markers, concepts, cognitive maps, natural-language mediators, kernel sentences, relational rules, nodes, associations, propositions, higher-order memory units, and features. (Eysenck, 1977, p. 4)

   6) The Problem with the Memory Metaphor

   The problem with the memory metaphor is that storage and retrieval of traces only deals [ sic] with old, previously articulated information. Memory traces can perhaps provide a basis for dealing with the "sameness" of the present experience with previous experiences, but the memory metaphor has no mechanisms for dealing with novel information. (Bransford, McCarrell, Franks & Nitsch, 1977, p. 434)

   7) The Results of a Hundred Years of the Psychological Study of Memory Are Somewhat Discouraging

   The results of a hundred years of the psychological study of memory are somewhat discouraging. We have established firm empirical generalisations, but most of them are so obvious that every ten-year-old knows them anyway. We have made discoveries, but they are only marginally about memory; in many cases we don't know what to do with them, and wear them out with endless experimental variations. We have an intellectually impressive group of theories, but history offers little confidence that they will provide any meaningful insight into natural behavior. (Neisser, 1978, pp. 12-13)

   8) The Structure and Function of a Schema in Memory

   A schema, then is a data structure for representing the generic concepts stored in memory. There are schemata representing our knowledge about all concepts; those underlying objects, situations, events, sequences of events, actions and sequences of actions. A schema contains, as part of its specification, the network of interrelations that is believed to normally hold among the constituents of the concept in question. A schema theory embodies a prototype theory of meaning. That is, inasmuch as a schema underlying a concept stored in memory corresponds to the mean ing of that concept, meanings are encoded in terms of the typical or normal situations or events that instantiate that concept. (Rumelhart, 1980, p. 34)

   9) Competence and Performance in Theories of Memory

   Memory appears to be constrained by a structure, a "syntax," perhaps at quite a low level, but it is free to be variable, deviant, even erratic at a higher level....

   Like the information system of language, memory can be explained in part by the abstract rules which underlie it, but only in part. The rules provide a basic competence, but they do not fully determine performance. (Campbell, 1982, pp. 228, 229)

    10) Metaphors of Memory

   When people think about the mind, they often liken it to a physical space, with memories and ideas as objects contained within that space. Thus, we speak of ideas being in the dark corners or dim recesses of our minds, and of holding ideas in mind. Ideas may be in the front or back of our minds, or they may be difficult to grasp. With respect to the processes involved in memory, we talk about storing memories, of searching or looking for lost memories, and sometimes of finding them. An examination of common parlance, therefore, suggests that there is general adherence to what might be called the spatial metaphor. The basic assumptions of this metaphor are that memories are treated as objects stored in specific locations within the mind, and the retrieval process involves a search through the mind in order to find specific memories....

   However, while the spatial metaphor has shown extraordinary longevity, there have been some interesting changes over time in the precise form of analogy used. In particular, technological advances have inﬂuenced theoretical conceptualisations.... The original Greek analogies were based on wax tablets and aviaries; these were superseded by analogies involving switchboards, gramophones, tape recorders, libraries, conveyor belts, and underground maps. Most recently, the workings of human memory have been compared to computer functioning... and it has been suggested that the various memory stores found in computers have their counterparts in the human memory system. (Eysenck, 1984, pp. 79-80)

    11) Comparison of Primary Memory and Secondary Memory

   Primary memory [as proposed by William James] relates to information that remains in consciousness after it has been perceived, and thus forms part of the psychological present, whereas secondary memory contains information about events that have left consciousness, and are therefore part of the psychological past. (Eysenck, 1984, p. 86)

    12) Semantic Memory and Episodic Memory

   Once psychologists began to study long-term memory per se, they realized it may be divided into two main categories.... Semantic memories have to do with our general knowledge about the working of the world. We know what cars do, what stoves do, what the laws of gravity are, and so on. Episodic memories are largely events that took place at a time and place in our personal history. Remembering specific events about our own actions, about our family, and about our individual past falls into this category. With amnesia or in aging, what dims... is our personal episodic memories, save for those that are especially dear or painful to us. Our knowledge of how the world works remains pretty much intact. (Gazzaniga, 1988, p. 42)

    13) The Relation of Memory to Thinking

   The nature of memory... provides a natural starting point for an analysis of thinking. Memory is the repository of many of the beliefs and representations that enter into thinking, and the retrievability of these representations can limit the quality of our thought. (Smith, 1990, p. 1)

Historical dictionary of quotations in cognitive science > Memory
13 lógica

lógica sustantivo femenino logic
lógico,-a adjetivo logical: es lógico que te enfades, it's natural for you to get angry
lógica sustantivo femenino logic: está fuera de toda lógica, it's completely illogical ' lógica' also found in these entries: Spanish: sentida - sentido - aplastante - encontrar English: add up - logic - rationale - hold

English-spanish dictionary > lógica
14 language

язык || языковой

- absolute language
- action description language
- actual machine language
- agent programming language
- AI language
- Algol-like language
- algorithmical language
- algorithmic language
- application-oriented language
- applicative language
- artificial language
- assembler language
- assembly language
- assembly-output language
- assignment-free language
- behavioral language
- bidirectional language
- block-structured language
- Boolean-based language
- business definition language
- business-oriented language
- calculus-type language
- C-based language
- client-side language
- code language
- command language
- compiled language
- compiler language
- component definition language
- composite language
- computer language
- computer-dependent language
- computer-independent language
- computer-oriented language
- computer-programming language
- computer-sensitive language
- consensus language
- context-free language
- control language
- conversational language
- core language
- data definition language
- data description language
- data language
- data manipulation language
- data storage description language
- database language
- data-entry language
- data-flow language
- data-query language
- declarative language
- defining language
- descriptive language
- descriptor language
- design language
- device media control language
- direct execution language
- directly interpretable language
- Dyck language
- end-user language
- escape language
- evolutive language
- executive-control language
- executive language
- explicit language
- extensible language
- fabricated language
- finite state language
- flow language
- foreign language
- formalized language
- frame-based language
- freestanding language
- functional language
- generated language
- graphics language
- graph-oriented language
- hardware-description language
- hardware language
- higher-level language
- higher-order language
- host language
- human language
- human-oriented language
- human-readable language
- indexed language
- information retrieval language
- informational language
- information language
- inherently ambiguous language
- input language
- input/output language
- instruction language
- integrated language
- interactive language
- interim language
- intermediate language
- internal language
- interpreted language
- job control language
- job-oriented language
- knowledge representation language
- language pair
- letter-equivalent languages
- linear language
- linear-programming language
- list-processing language
- logic-type language
- low-level language
- machine language
- machine-dependent language
- machine-independent language
- machine-oriented language
- macroassembly language
- macro language
- macroinstruction language
- macroprogramming language
- man-to-computer language
- mathematical formular language
- memory management language
- mnemonic language
- modeling language
- native language
- natural language
- NC programming language
- nested language
- network-oriented language
- nonprocedural language
- numder language
- object language
- object modeling language
- object-oriented language
- one-dimensional language
- operator-oriented language
- original language
- page description language
- parallel language
- phrase structure language
- predicate language
- predicate logic-based language
- predicate logic language
- privacy language
- problem statement language
- problem-oriented language
- procedural language
- procedure-oriented language
- process control language
- production language
- program language
- programming language
- pseudo language
- pseudomachine language
- query language
- readable specification language
- reference language
- regular language
- relational language
- relational-type language
- representation language
- representation language

- requirement statement language
- requirements modeling language
- restricted language
- rule-based language
- ruly language
- schema language
- science-oriented language
- script language
- self-contained language
- semantic-formal language
- semiformal language
- sentential language
- serial language
- simulation language
- single-assignment language
- source language
- specialized language
- specification language
- stream-based language
- strict language
- structured programming language
- structured query language
- super language
- super-high-level language
- symbolic language
- symbolic programming language
- syntax language
- synthetic language
- system input language
- system language
- system-oriented language
- tabular language
- target language
- TC language
- time sharing language
- type-free language
- unified modeling language
- update language
- user language
- user-oriented language
- very-high-level language

English-Russian dictionary of computer science and programming > language
15 unit

1) единица; единое целое

2) единица измерения

3) устройство; узел; блок; прибор; звено; элемент (см. тж component, device, element)

4) компонента программы, модуль

•

- actuating unit
- addressing unit
- address unit
- add-subtract control unit
- allocation unit
- alphanumeric unit
- alphameric unit
- analog operational unit
- analog switching unit
- arithmetic and logic unit
- arithmetic control unit
- arithmetic unit
- arithmetic/logic unit
- assembly unit
- assigned unit
- audio response unit
- automatic calling unit
- availability control unit
- available unit
- bad unit
- bistable unit
- buffer unit
- bus guardian unit
- card punching unit
- card-reader unit
- cassette-loaded magnetic tape unit
- central processing unit
- central processor unit
- central terminal unit
- channel control unit
- clock unit
- cluster tape unit
- coefficient unit
- collating unit
- collator unit
- column-shift unit
- comparator unit
- comparing unit
- computing unit
- configuration control unit
- consistent unit
- constant multiplier coefficient unit
- control unit
- coordinate conversion unit
- core storage unit
- data acquisition unit
- data adapter unit
- data collection unit
- data display unit
- data handling unit
- data unit
- delay unit
- detached unit
- differentiating unit
- digital counting unit
- digital time unit
- direct-access unit
- disbursting unit
- disk unit
- display unit
- division unit
- elementary unit
- engineering unit
- equality unit
- essential unit
- executive unit
- fast unit
- feedback unit
- file unit
- forming unit
- fractional arithmetic unit
- free-standing tape unit
- functional unit
- fundamental unit
- gate unit
- generic program unit
- generic unit
- gold unit
- graphical display unit
- graphic display unit
- hard-disk unit
- identity unit
- impossible unit
- incremental tape unit
- indexing unit
- information content binary unit
- information content decimal unit
- information content natural unit
- information unit
- input unit
- input-output unit
- inquiry unit
- instruction control unit
- instruction fetch unit
- instruction unit
- integrating unit
- interface unit
- interrogation unit
- key punch unit
- key-to-disk unit
- key-to-tape unit
- known good unit
- lag unit
- lexical unit
- library unit
- line interface unit
- linear unit
- linguistic unit
- locking unit
- logical unit
- logic unit
- magnetic tape unit
- magnetic-tape file unit
- main control unit
- manageable unit
- manual input unit
- manual word unit
- master units
- memory control unit
- memory management unit
- memory unit
- micrologic unit
- microprocessor based unit
- microprocessor unit
- microprocessor-controlled unit
- microprogram unit
- microprogrammed unit
- modem sharing unit
- modular unit
- monitor unit
- multiplication-division unit
- multiplier unit
- multiply-divide unit
- multiplying unit
- multistation access unit
- network control unit
- off unit
- off-line unit
- on unit
- on-line unit
- operational unit
- operator interface unit
- output unit
- packet-switching unit
- paragraph unit
- parallel arithmetic unit
- peripheral control unit
- peripheral unit
- photographic printing unit
- physical unit
- pluggable unit
- plug-in unit
- plug-to-plug compatible unit
- polygon-filling unit
- port sharing unit
- power distribution unit
- power supply unit
- power unit
- printing unit
- processing unit
- program control unit
- program unit
- protocol unit
- punched card unit
- punch card unit
- punching unit
- query unit
- reader unit
- read-punch unit
- read-write unit
- recovery unit
- referable unit
- remote display unit
- remote entry unit
- reproducing unit
- retirement unit
- ripple through carry unit
- sample unit
- sampling unit
- scaling unit
- segregating unit
- selection channel control unit
- self-contained unit
- semantic unit
- sensing unit
- sensory unit
- serial arithmetic unit
- setup unit
- set unit
- shaping unit
- shared unit
- smallest recoverable unit
- stand-alone unit
- static unit
- storage control unit
- storage unit
- stream unit
- subtracting unit
- summary punching unit
- summing unit
- supply unit
- switching unit
- switchover unit
- symbolic unit
- syntactical unit
- syntactic unit
- system control unit
- system input unit
- system output unit
- tape cartridge unit
- tape control unit
- tape selection unit
- tape unit
- telecommunications control unit
- telephone communication unit
- terminal unit
- time unit
- timing unit
- transmission control unit
- transport unit
- unit of allocation
- unit of language
- unit of operation
- variable speed tape unit
- vertical format unit
- visual display unit
- voice recognition unit

English-Russian dictionary of computer science and programming > unit
16 Philosophy

   1) There Are Ideas That Have Their Own True and Immutable Nature

   And what I believe to be more important here is that I find in myself an infinity of ideas of certain things which cannot be assumed to be pure nothingness, even though they may have perhaps no existence outside of my thought. These things are not figments of my imagination, even though it is within my power to think of them or not to think of them; on the contrary, they have their own true and immutable natures. Thus, for example, when I imagine a triangle, even though there may perhaps be no such figure anywhere in the world outside of my thought, nor ever have been, nevertheless the figure cannot help having a certain determinate nature... or essence, which is immutable and eternal, which I have not invented and which does not in any way depend upon my mind. (Descartes, 1951, p. 61)

   2) Examine What Is within Our Reach

   Let us console ourselves for not knowing the possible connections between a spider and the rings of Saturn, and continue to examine what is within our reach. (Voltaire, 1961, p. 144)

   3) Modern Philosophy Starts with the Cartesian Catastrophe

   As modern physics started with the Newtonian revolution, so modern philosophy starts with what one might call the Cartesian Catastrophe. The catastrophe consisted in the splitting up of the world into the realms of matter and mind, and the identification of "mind" with conscious thinking. The result of this identification was the shallow rationalism of l'esprit Cartesien, and an impoverishment of psychology which it took three centuries to remedy even in part. (Koestler, 1964, p. 148)

   4) The Rightful Claims of Philosophy

   It has been made of late a reproach against natural philosophy that it has struck out on a path of its own, and has separated itself more and more widely from the other sciences which are united by common philological and historical studies. The opposition has, in fact, been long apparent, and seems to me to have grown up mainly under the inﬂuence of the Hegelian philosophy, or, at any rate, to have been brought out into more distinct relief by that philosophy.... The sole object of Kant's "Critical Philosophy" was to test the sources and the authority of our knowledge, and to fix a definite scope and standard for the researches of philosophy, as compared with other sciences.... [But Hegel's] "Philosophy of Identity" was bolder. It started with the hypothesis that not only spiritual phenomena, but even the actual world-nature, that is, and man-were the result of an act of thought on the part of a creative mind, similar, it was supposed, in kind to the human mind.... The philosophers accused the scientific men of narrowness; the scientific men retorted that the philosophers were crazy. And so it came about that men of science began to lay some stress on the banishment of all philosophic inﬂuences from their work; while some of them, including men of the greatest acuteness, went so far as to condemn philosophy altogether, not merely as useless, but as mischievous dreaming. Thus, it must be confessed, not only were the illegitimate pretensions of the Hegelian system to subordinate to itself all other studies rejected, but no regard was paid to the rightful claims of philosophy, that is, the criticism of the sources of cognition, and the definition of the functions of the intellect. (Helmholz, quoted in Dampier, 1966, pp. 291-292)

   5) The Philosophy of Philosophy

   Philosophy remains true to its classical tradition by renouncing it. (Habermas, 1972, p. 317)

   6) Philosophy Is a Field Which Has Certain Central Questions

   I have not attempted... to put forward any grand view of the nature of philosophy; nor do I have any such grand view to put forth if I would. It will be obvious that I do not agree with those who see philosophy as the history of "howlers" and progress in philosophy as the debunking of howlers. It will also be obvious that I do not agree with those who see philosophy as the enterprise of putting forward a priori truths about the world.... I see philosophy as a field which has certain central questions, for example, the relation between thought and reality.... It seems obvious that in dealing with these questions philosophers have formulated rival research programs, that they have put forward general hypotheses, and that philosophers within each major research program have modified their hypotheses by trial and error, even if they sometimes refuse to admit that that is what they are doing. To that extent philosophy is a "science." To argue about whether philosophy is a science in any more serious sense seems to me to be hardly a useful occupation.... It does not seem to me important to decide whether science is philosophy or philosophy is science as long as one has a conception of both that makes both essential to a responsible view of the world and of man's place in it. (Putnam, 1975, p. xvii)

   7) The Central Task of Philosophy

   What can philosophy contribute to solving the problem of the relation [of] mind to body? Twenty years ago, many English-speaking philosophers would have answered: "Nothing beyond an analysis of the various mental concepts." If we seek knowledge of things, they thought, it is to science that we must turn. Philosophy can only cast light upon our concepts of those things.

   This retreat from things to concepts was not undertaken lightly. Ever since the seventeenth century, the great intellectual fact of our culture has been the incredible expansion of knowledge both in the natural and in the rational sciences (mathematics, logic).

   The success of science created a crisis in philosophy. What was there for philosophy to do? Hume had already perceived the problem in some degree, and so surely did Kant, but it was not until the twentieth century, with the Vienna Circle and with Wittgenstein, that the difficulty began to weigh heavily. Wittgenstein took the view that philosophy could do no more than strive to undo the intellectual knots it itself had tied, so achieving intellectual release, and even a certain illumination, but no knowledge. A little later, and more optimistically, Ryle saw a positive, if reduced role, for philosophy in mapping the "logical geography" of our concepts: how they stood to each other and how they were to be analyzed....

   Since that time, however, philosophers in the "analytic" tradition have swung back from Wittgensteinian and even Rylean pessimism to a more traditional conception of the proper role and tasks of philosophy. Many analytic philosophers now would accept the view that the central task of philosophy is to give an account, or at least play a part in giving an account, of the most general nature of things and of man. (Armstrong, 1990, pp. 37-38)

   8) Philosophy's Evolving Engagement with Artificial Intelligence and Cognitive Science

   In the beginning, the nature of philosophy's engagement with artificial intelligence and cognitive science was clear enough. The new sciences of the mind were to provide the long-awaited vindication of the most potent dreams of naturalism and materialism. Mind would at last be located firmly within the natural order. We would see in detail how the most perplexing features of the mental realm could be supported by the operations of solely physical laws upon solely physical stuff. Mental causation (the power of, e.g., a belief to cause an action) would emerge as just another species of physical causation. Reasoning would be understood as a kind of automated theorem proving. And the key to both was to be the depiction of the brain as the implementation of multiple higher level programs whose task was to manipulate and transform symbols or representations: inner items with one foot in the physical (they were realized as brain states) and one in the mental (they were bearers of contents, and their physical gymnastics were cleverly designed to respect semantic relationships such as truth preservation). (A. Clark, 1996, p. 1)

   9) The Enduring Value of Philosophy

   Socrates of Athens famously declared that "the unexamined life is not worth living," and his motto aptly explains the impulse to philosophize. Taking nothing for granted, philosophy probes and questions the fundamental presuppositions of every area of human inquiry.... [P]art of the job of the philosopher is to keep at a certain critical distance from current doctrines, whether in the sciences or the arts, and to examine instead how the various elements in our world-view clash, or fit together. Some philosophers have tried to incorporate the results of these inquiries into a grand synoptic view of the nature of reality and our human relationship to it. Others have mistrusted system-building, and seen their primary role as one of clarifications, or the removal of obstacles along the road to truth. But all have shared the Socratic vision of using the human intellect to challenge comfortable preconceptions, insisting that every aspect of human theory and practice be subjected to continuing critical scrutiny....

   Philosophy is, of course, part of a continuing tradition, and there is much to be gained from seeing how that tradition originated and developed. But the principal object of studying the materials in this book is not to pay homage to past genius, but to enrich one's understanding of central problems that are as pressing today as they have always been-problems about knowledge, truth and reality, the nature of the mind, the basis of right action, and the best way to live. These questions help to mark out the territory of philosophy as an academic discipline, but in a wider sense they define the human predicament itself; they will surely continue to be with us for as long as humanity endures. (Cottingham, 1996, pp. xxi-xxii)

    10) The Distinction between Dionysian Man and Apollonian Man, between Art and Creativity and Reason and Self- Control

   In his study of ancient Greek culture, The Birth of Tragedy, Nietzsche drew what would become a famous distinction, between the Dionysian spirit, the untamed spirit of art and creativity, and the Apollonian, that of reason and self-control. The story of Greek civilization, and all civilizations, Nietzsche implied, was the gradual victory of Apollonian man, with his desire for control over nature and himself, over Dionysian man, who survives only in myth, poetry, music, and drama. Socrates and Plato had attacked the illusions of art as unreal, and had overturned the delicate cultural balance by valuing only man's critical, rational, and controlling consciousness while denigrating his vital life instincts as irrational and base. The result of this division is "Alexandrian man," the civilized and accomplished Greek citizen of the later ancient world, who is "equipped with the greatest forces of knowledge" but in whom the wellsprings of creativity have dried up. (Herman, 1997, pp. 95-96)

Historical dictionary of quotations in cognitive science > Philosophy
17 LM

1) Компьютерная техника: L M, List Messages, Local Macro

2) Геология: Meander length of river or stream

3) Медицина: left main

4) Американизм: Land Mean, Lost Minions

5) Военный термин: Legion of Merit, Light Map, Loss Of Material, land time, launch mount, lethal material, light maintenance, lightweight machinegun

6) Техника: labor management, line man, line mortar, locator, middle

7) Шутливое выражение: Living Marxism

8) Химия: Lithium Manganese, Lower Melting

9) Метеорология: Low Melt

10) Железнодорожный термин: Union Pacific Railroad Company

11) Астрономия: Low Mass

12) Биржевой термин: Liquidity And Money

13) Горное дело: обозначение стандарта тонкостенного бурового инструмента для алмазного бурения (США)

14) Телевидение: loading motor

15) Телекоммуникации: низкая середина (полоса частот)

16) Сокращение: Last Month, Licentiate in Medicine, Lord Mayor, left male, list of material, Lunar Module (Apollo spacecraft; a.k.a. LEM), Life Master (Contract Bridge ranking), Labor Month, LadderMonkey (gaming league), Ladies' Meeting, Lady Macbeth, Lady Madonna (Beatles song), Lagrange Multiplier, Lambert(s) (unit of luminance), LanManager, Language Minority (language learning), Laser Module, Lata Mangeshkar (Indian singer), Lateral Meniscus (knee), Lauis Metis (neutral zone planet from Diaspora), Lay Midwife (midwife without a medical degree), Le Mans, Lead Man (Supervisor), Leaky Mode (transmission line), Left Message, Legal Momentum (formerly NOW Legal Defense and Education Fund), Levenberg-Marquardt (algorithm), Libris Mortis (roleplaying games, Dungeons & Dragons), Licensed Midwife, Life Master (Contract Bridge Ranking), Life Member, Lifetime Maintenance, Light Magnum (ammunition), Light Meter (photography), Lightwave Multimeter (Agilent), Line Monitor, Linux Magazine, Linux-Mandrake (Linux Distribution), Liquid Metal, Liquidity-Money (macroeconomic curve that links interest rates and output as a result of interactions in asset markets), List of Material/s, Litchfield and Madison Railroad, Littlewood and Miller (probabilistic model), Load Multiple (IBM), Loadmaster, Local Manufacture, Location Management, Lockheed Martin, Logic Module, Logistics Management, Logistics Manager, Loop Modem, Lorenz-Mie, LoudMusic, Love Marriage, Low Migration (printing ink), Low Moment (chemistry), Lowell Massachussets (.50 caliber ammunition headstamp), Luigi's Mansion (video game), Lumbering Might (computer game), Lunar Magic (game), Lunar Module (replaced LEM), Lunch Menu, Lunixmonster (Natural Selection gaming server), liver metastasis

17) Университет: Lab Manual, Learner Model

18) Физика: Light Meter

19) Электроника: Leaky Mode, Light Microscopy, Linear Monolithic

20) Вычислительная техника: Lunar Module (a.k.a. LEM, Apollo spacecraft, Space), локальная ЭВМ (local machine), локальная машина (local machine)

21) Нефть: lime

22) Биохимия: Light Microscope

23) Банковское дело: кривая, характеризующая равновесный уровень дохода и процента на рынке денег (liquidity preference money curve)

24) Транспорт: Left Motor

25) Экология: Meander length or river or stream

26) Деловая лексика: Labor Managed, Linear Model

27) Глоссарий компании Сахалин Энерджи: linear meter, load moment

28) Образование: Language Minority

29) Инвестиции: liquidity preference money curve

30) Сетевые технологии: Local Machine, Lock Manager

31) Полимеры: low-modulus, low-molecular

32) Программирование: Load Math

33) Автоматика: language for manipulation, linear motion

34) Контроль качества: laboratory evaluation

35) Нефть и газ: estimated equivalent dead time, logic manager

36) Электротехника: latch magnet, load management

37) Имена и фамилии: Leonard Michaels, Lord Michael

38) Должность: Leisure Monitor

39) Чат: Love Mode

40) NYSE. Legg Mason, Inc.

41) НАСА: Lunar Module

42) Программное обеспечение: Lan Manager, Lisp Maintainer

43) Единицы измерений: Long Metre

Универсальный англо-русский словарь > LM
18 Lm

1) Компьютерная техника: L M, List Messages, Local Macro

2) Геология: Meander length of river or stream

3) Медицина: left main

4) Американизм: Land Mean, Lost Minions

5) Военный термин: Legion of Merit, Light Map, Loss Of Material, land time, launch mount, lethal material, light maintenance, lightweight machinegun

6) Техника: labor management, line man, line mortar, locator, middle

7) Шутливое выражение: Living Marxism

8) Химия: Lithium Manganese, Lower Melting

9) Метеорология: Low Melt

10) Железнодорожный термин: Union Pacific Railroad Company

11) Астрономия: Low Mass

12) Биржевой термин: Liquidity And Money

13) Горное дело: обозначение стандарта тонкостенного бурового инструмента для алмазного бурения (США)

14) Телевидение: loading motor

15) Телекоммуникации: низкая середина (полоса частот)

16) Сокращение: Last Month, Licentiate in Medicine, Lord Mayor, left male, list of material, Lunar Module (Apollo spacecraft; a.k.a. LEM), Life Master (Contract Bridge ranking), Labor Month, LadderMonkey (gaming league), Ladies' Meeting, Lady Macbeth, Lady Madonna (Beatles song), Lagrange Multiplier, Lambert(s) (unit of luminance), LanManager, Language Minority (language learning), Laser Module, Lata Mangeshkar (Indian singer), Lateral Meniscus (knee), Lauis Metis (neutral zone planet from Diaspora), Lay Midwife (midwife without a medical degree), Le Mans, Lead Man (Supervisor), Leaky Mode (transmission line), Left Message, Legal Momentum (formerly NOW Legal Defense and Education Fund), Levenberg-Marquardt (algorithm), Libris Mortis (roleplaying games, Dungeons & Dragons), Licensed Midwife, Life Master (Contract Bridge Ranking), Life Member, Lifetime Maintenance, Light Magnum (ammunition), Light Meter (photography), Lightwave Multimeter (Agilent), Line Monitor, Linux Magazine, Linux-Mandrake (Linux Distribution), Liquid Metal, Liquidity-Money (macroeconomic curve that links interest rates and output as a result of interactions in asset markets), List of Material/s, Litchfield and Madison Railroad, Littlewood and Miller (probabilistic model), Load Multiple (IBM), Loadmaster, Local Manufacture, Location Management, Lockheed Martin, Logic Module, Logistics Management, Logistics Manager, Loop Modem, Lorenz-Mie, LoudMusic, Love Marriage, Low Migration (printing ink), Low Moment (chemistry), Lowell Massachussets (.50 caliber ammunition headstamp), Luigi's Mansion (video game), Lumbering Might (computer game), Lunar Magic (game), Lunar Module (replaced LEM), Lunch Menu, Lunixmonster (Natural Selection gaming server), liver metastasis

17) Университет: Lab Manual, Learner Model

18) Физика: Light Meter

19) Электроника: Leaky Mode, Light Microscopy, Linear Monolithic

20) Вычислительная техника: Lunar Module (a.k.a. LEM, Apollo spacecraft, Space), локальная ЭВМ (local machine), локальная машина (local machine)

21) Нефть: lime

22) Биохимия: Light Microscope

23) Банковское дело: кривая, характеризующая равновесный уровень дохода и процента на рынке денег (liquidity preference money curve)

24) Транспорт: Left Motor

25) Экология: Meander length or river or stream

26) Деловая лексика: Labor Managed, Linear Model

27) Глоссарий компании Сахалин Энерджи: linear meter, load moment

28) Образование: Language Minority

29) Инвестиции: liquidity preference money curve

30) Сетевые технологии: Local Machine, Lock Manager

31) Полимеры: low-modulus, low-molecular

32) Программирование: Load Math

33) Автоматика: language for manipulation, linear motion

34) Контроль качества: laboratory evaluation

35) Нефть и газ: estimated equivalent dead time, logic manager

36) Электротехника: latch magnet, load management

37) Имена и фамилии: Leonard Michaels, Lord Michael

38) Должность: Leisure Monitor

39) Чат: Love Mode

40) NYSE. Legg Mason, Inc.

41) НАСА: Lunar Module

42) Программное обеспечение: Lan Manager, Lisp Maintainer

43) Единицы измерений: Long Metre

Универсальный англо-русский словарь > Lm
19 lm

1) Компьютерная техника: L M, List Messages, Local Macro

2) Геология: Meander length of river or stream

3) Медицина: left main

4) Американизм: Land Mean, Lost Minions

5) Военный термин: Legion of Merit, Light Map, Loss Of Material, land time, launch mount, lethal material, light maintenance, lightweight machinegun

6) Техника: labor management, line man, line mortar, locator, middle

7) Шутливое выражение: Living Marxism

8) Химия: Lithium Manganese, Lower Melting

9) Метеорология: Low Melt

10) Железнодорожный термин: Union Pacific Railroad Company

11) Астрономия: Low Mass

12) Биржевой термин: Liquidity And Money

13) Горное дело: обозначение стандарта тонкостенного бурового инструмента для алмазного бурения (США)

14) Телевидение: loading motor

15) Телекоммуникации: низкая середина (полоса частот)

16) Сокращение: Last Month, Licentiate in Medicine, Lord Mayor, left male, list of material, Lunar Module (Apollo spacecraft; a.k.a. LEM), Life Master (Contract Bridge ranking), Labor Month, LadderMonkey (gaming league), Ladies' Meeting, Lady Macbeth, Lady Madonna (Beatles song), Lagrange Multiplier, Lambert(s) (unit of luminance), LanManager, Language Minority (language learning), Laser Module, Lata Mangeshkar (Indian singer), Lateral Meniscus (knee), Lauis Metis (neutral zone planet from Diaspora), Lay Midwife (midwife without a medical degree), Le Mans, Lead Man (Supervisor), Leaky Mode (transmission line), Left Message, Legal Momentum (formerly NOW Legal Defense and Education Fund), Levenberg-Marquardt (algorithm), Libris Mortis (roleplaying games, Dungeons & Dragons), Licensed Midwife, Life Master (Contract Bridge Ranking), Life Member, Lifetime Maintenance, Light Magnum (ammunition), Light Meter (photography), Lightwave Multimeter (Agilent), Line Monitor, Linux Magazine, Linux-Mandrake (Linux Distribution), Liquid Metal, Liquidity-Money (macroeconomic curve that links interest rates and output as a result of interactions in asset markets), List of Material/s, Litchfield and Madison Railroad, Littlewood and Miller (probabilistic model), Load Multiple (IBM), Loadmaster, Local Manufacture, Location Management, Lockheed Martin, Logic Module, Logistics Management, Logistics Manager, Loop Modem, Lorenz-Mie, LoudMusic, Love Marriage, Low Migration (printing ink), Low Moment (chemistry), Lowell Massachussets (.50 caliber ammunition headstamp), Luigi's Mansion (video game), Lumbering Might (computer game), Lunar Magic (game), Lunar Module (replaced LEM), Lunch Menu, Lunixmonster (Natural Selection gaming server), liver metastasis

17) Университет: Lab Manual, Learner Model

18) Физика: Light Meter

19) Электроника: Leaky Mode, Light Microscopy, Linear Monolithic

20) Вычислительная техника: Lunar Module (a.k.a. LEM, Apollo spacecraft, Space), локальная ЭВМ (local machine), локальная машина (local machine)

21) Нефть: lime

22) Биохимия: Light Microscope

23) Банковское дело: кривая, характеризующая равновесный уровень дохода и процента на рынке денег (liquidity preference money curve)

24) Транспорт: Left Motor

25) Экология: Meander length or river or stream

26) Деловая лексика: Labor Managed, Linear Model

27) Глоссарий компании Сахалин Энерджи: linear meter, load moment

28) Образование: Language Minority

29) Инвестиции: liquidity preference money curve

30) Сетевые технологии: Local Machine, Lock Manager

31) Полимеры: low-modulus, low-molecular

32) Программирование: Load Math

33) Автоматика: language for manipulation, linear motion

34) Контроль качества: laboratory evaluation

35) Нефть и газ: estimated equivalent dead time, logic manager

36) Электротехника: latch magnet, load management

37) Имена и фамилии: Leonard Michaels, Lord Michael

38) Должность: Leisure Monitor

39) Чат: Love Mode

40) NYSE. Legg Mason, Inc.

41) НАСА: Lunar Module

42) Программное обеспечение: Lan Manager, Lisp Maintainer

43) Единицы измерений: Long Metre

Универсальный англо-русский словарь > lm
20 function

1) функция

2) функционировать; находиться в работоспособном состоянии

3) выполнять функцию; играть роль

4) (дополнительное) функциональное устройство, проф. функция ( в стандарте USB)

5) вчт. отображение || отображать

•

- activation function
- actuating transfer function
- additive function
- additive/multiplicative function
- admittance function
- advanced communication function
- affine Boolean function
- aggregate function
- algebraic function
- all-pass transfer function
- all-pole function
- all-zero function
- alternating function
- ambiguity function
- amplitude distribution function
- amplitude function
- AM-tive function additive/multiplicative function
- anode work function
- aperture phase function
- apodizing function
- application program function
- autocorrelation function
- automatic azimuth alignment function
- band-limited function
- base station control function
- basis function
- Bellman function
- bent function
- Bessel function of imaginary argument
- Bessel function
- beta function
- bijection function
- bijective function
- binary activation function
- binary sigmoid function
- binate function
- bipolar sigmoid function
- bi-state function
- bivariate distribution function
- Boolean function
- Bose-Einstein distribution function
- bounded function
- boxcar function
- Brillouin function
- built-in function
- Butterworth function
- carpet function
- carrier function
- cathode work function
- characteristic function
- circular function
- closed function
- closed-loop transfer function
- clutching function
- coherence function
- color matching functions
- comb function
- combination function
- combining function
- competitive function
- complementary error function
- complementary function
- composite function
- computable function
- concentrated likelihood function
- continuous function
- contrast transfer function
- control function
- convolution function
- correlation function
- cost function
- covariance generating function
- criterion function
- cross-correlation function
- cryptographic hash-function

- cumulative distribution function
- current potential function
- current transfer function
- curried function
- data communications function
- data-path function
- decision function
- degate function
- degating function
- delta function
- demand function
- density function
- descrambling function
- describing function
- difference transfer function
- differentiable function
- digamma function
- Dirac delta function
- Dirac function
- disconnect-reconnect function
- discriminant function
- distribution function
- driving-point function
- eikonal function
- electron wave function
- embedding function
- encryption function
- ergodic function
- error function
- excitation function
- explicit function
- exponential function
- extensional function
- external function
- failure density function
- feedback transfer function
- Fermi function
- Fermi-Dirac distribution function
- force function
- forward transfer function
- frequency function
- frequency-generating function
- frequency-response function
- friend function
- FS function
- full-speed function
- fuzzy function
- fuzzy objective function
- fuzzy utility function
- gage function
- Gaussian function
- Gaussian radial basis function
- generalized function
- generic function
- global implicit function
- global inverse function
- Green functions
- Green's function
- Hamilton function
- Hankel function
- hard limit activation function
- hash-function

- hashing function
- hazard function
- head-related transfer function
- Heaviside step function
- Huber function
- hyperbolic function
- hyperbolic tangent activation function
- idempotent function
- image function
- impedance function
- implicit function
- injection function
- injective function
- inline function
- intensional function
- interference function
- interworking function
- inverse distribution function
- inverse function
- invertible mapping function
- inverting function
- kernel function
- Lagrange's function
- Langevin function
- latent function
- Legendre associated function of the first kind
- Legendre associated function of the second kind
- Legendre function of the first kind
- Legendre function of the second kind
- lexical function
- likelihood function
- line search function
- linear function
- linear logic function
- logic function
- logistic function
- logistic sigmoid function
- log-likelihood function
- log-linear function
- log-log function
- look-up function
- loss function
- low-speed function
- LS function
- luminosity function
- macro function
- main function
- maintenance entity function
- majorized function
- majorizing function
- mapping function
- Markov function
- mathematical function
- member function
- membership function
- memo function
- memoised function
- memoized function
- minorized function
- minorizing function
- modified Bessel function
- modular hash-function
- modulating function
- modulation transfer function
- moment-generating function
- monotonic function
- Morse function
- multi-input multi-output transfer function
- multi-valued function
- multivariate distribution function
- mutual coherence function
- natural trigonometric function
- never-decreasing function
- never-increasing function
- non-decreasing function
- non-increasing function
- nonlinear function
- normalized Gaussian radial basis function
- normalized radial basis functions with equal heights
- normalized radial basis functions with equal volumes
- normalized radial basis functions with equal widths and heights
- normalized radial basis functions with equal widths
- normalized radial basis functions with unequal widths and heights
- objective function
- one-one function
- one-to-one function
- one-way function
- one-way hash function
- open-loop transfer function
- optical transfer function
- ordinary Gaussian radial basis function
- ordinary radial basis functions with equal widths
- ordinary radial basis functions with unequal widths
- orthogonal functions
- overlapped functions
- partial autocorrelation function
- penalty function
- perfect hash-function
- phase transfer function
- photoelectric work function
- photopic response function
- piecewise constant function
- piecewise linear function
- piecewise polynomial function
- Pierce function
- point-spread function
- polynomial function
- positive linear function
- postsynaptic potential function
- power function of test
- power function
- predefined function
- predicate function
- probability density function
- probability function
- probability mass function
- production function
- projection function
- projective function
- propagation function
- propositional function
- PSP function
- pulsating function
- pure virtual function
- quadratic error function
- radial basis function
- radial combination function
- ramp function
- range weighting function
- reactance function
- register function
- regression function
- resolvent function
- response function
- restricted function
- risk function
- saturating linear function
- scalar function
- scaling function
- scattering function
- scedastic function
- Schrödinger wave function
- scrambling function
- screen size-viewing distance function
- self-inverse function
- semilinear function
- sensing function
- sentential function
- shape function
- sigmoid activation function
- sigmoid function
- sign function
- signal function
- signum activation function
- signum function
- smooth function
- socket library function
- softmax activation function
- spectral density function
- spectral function
- spectral radiance function
- spline function
- spot function
- spread function
- square-integrable function
- square-law transfer function
- squashed sign function
- squashing function
- state function
- state query function
- steering function
- step function
- stream function
- summing function
- support entity function
- support function
- supported function
- surjection function
- surjective function
- survival function
- switch function
- switching function
- switch-type function
- symmetric saturating linear function
- tame function
- tan-sigmoid activation function
- target function
- tensor function
- tesseral function
- testing function
- tetragamma function
- thermionic work function
- threshold function
- through transfer function
- transcendental function
- transfer function
- trial function
- trigamma function
- trigonometric function
- tri-state function
- typematic function
- unate function
- uncurried function
- unit impulse function
- unit step function
- unsupported function
- user-defined function
- utility function
- vector function
- virtual function
- visibility function
- voltage potential function
- voltage transfer function
- Walsh functions
- wave function
- wave-number limited function
- weighting function
- window function
- work function

The New English-Russian Dictionary of Radio-electronics > function

Страницы

См. также в других словарях:

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natural logic

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Словари и энциклопедии на Академике

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natural logic

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