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1 automatic digital distribution frame
Computers: ADCZУниверсальный русско-английский словарь > automatic digital distribution frame
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2 automatic selection of digital electronic computers
Универсальный англо-русский словарь > automatic selection of digital electronic computers
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3 automatic selection of digital electronic computers
Engineering: ASDECУниверсальный русско-английский словарь > automatic selection of digital electronic computers
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4 Electronic Discrete Variable Automatic Computer
1) Computers: EDVAC2) File extension: EDVAC (First stored-program digital computer)Универсальный русско-английский словарь > Electronic Discrete Variable Automatic Computer
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5 Wilkes, Maurice Vincent
SUBJECT AREA: Electronics and information technology[br]b. 26 June 1913 Stourbridge, Worcestershire, England[br]English physicist who was jointly responsible for the construction of the EDS AC computer.[br]Educated at King Edward VI Grammar School, Stourbridge, where he began to make radio sets and read Wireless World, Wilkes went to St John's College, Cambridge, in 1931, graduating as a Wrangler in the Mathematical Tripos in 1934. He then carried out research at the Cavendish Laboratory, becoming a demonstrator in 1937. During the Second World War he worked on radar, differential analysers and operational research at the Bawdsey Research Station and other air-defence establishments. In 1945 he returned to Cambridge as a lecturer and as Acting Director of the Mathematical (later Computer) Laboratory, serving as Director from 1946 to 1970.During the late 1940s, following visits to the USA for computer courses and to see the ENIAC computer, with the collaboration of colleagues he constructed the Cambridge University digital computer EDSAC (for Electronic Delay Storage Automatic Computer), using ultrasonic delay lines for data storage. In the mid-1950s a second machine, EDSAC2, was constructed using a magnetic-core memory. In 1965 he became Professor of Computer Technology. After retirement he worked for the Digital Electronic Corporation (DEC) from 1981 to 1986, serving also as Adjunct Professor of Computer Science and Electrical Engineering at the Massachusetts Institute of Technology from 1981 to 1985. In 1990 he became a research strategy consultant to the Olivetti Research Directorate.[br]Principal Honours and DistinctionsFRS 1956. First President, British Computer Society 1957–60. Honorary DSc Munich 1978, Bath 1987. Honorary DTech Linkoping 1975. FEng 1976. Institution of Electrical Engineers Faraday Medal 1981.Bibliography1948, "The design of a practical high-speed computing machine", Proceedings of the Royal Society A195:274 (describes EDSAC).1949, Oscillation of the Earth's Atmosphere.1951, Preparation of Programs for an Electronic Digital Computer, New York: Addison-Wesley.1956, Automatic Digital Computers, London: Methuen. 1966, A Short Introduction to Numerical Analysis.1968, Time-Sharing Computer Systems: McDonald \& Jane's.1979, The Cambridge CAP Computer and its Operating System: H.Holland.1985, Memoirs of a Computer Pioneer, Cambridge, Mass.: MIT Press (autobiography).Further ReadingB.Randell (ed.), 1973, The Origins of Digital Computers, Berlin: Springer-Verlag.KFBiographical history of technology > Wilkes, Maurice Vincent
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6 автоматический коммутатор цифровых сигналов
Computers: automatic digital distribution frameУниверсальный русско-английский словарь > автоматический коммутатор цифровых сигналов
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7 Williams, Sir Frederic Calland
SUBJECT AREA: Electronics and information technology[br]b. 26 June 1911 Stockport, Cheshire, Englandd. 11 August 1977 Prestbury, Cheshire, England[br]English electrical engineer who invented the Williams storage cathode ray tube, which was extensively used worldwide as a data memory in the first digital computers.[br]Following education at Stockport Grammar School, Williams entered Manchester University in 1929, gaining his BSc in 1932 and MSc in 1933. After a short time as a college apprentice with Metropolitan Vickers, he went to Magdalen College, Oxford, to study for a DPhil, which he was awarded in 1936. He returned to Manchester University that year as an assistant lecturer, gaining his DSc in 1939. Following the outbreak of the Second World War he worked for the Scientific Civil Service, initially at the Bawdsey Research Station and then at the Telecommunications Research Establishment at Malvern, Worcestershire. There he was involved in research on non-incandescent amplifiers and diode rectifiers and the development of the first practical radar system capable of identifying friendly aircraft. Later in the war, he devised an automatic radar system suitable for use by fighter aircraft.After the war he resumed his academic career at Manchester, becoming Professor of Electrical Engineering and Director of the University Electrotechnical Laboratory in 1946. In the same year he succeeded in developing a data-memory device based on the cathode ray tube, in which the information was stored and read by electron-beam scanning of a charge-retaining target. The Williams storage tube, as it became known, not only found obvious later use as a means of storing single-frame, still television images but proved to be a vital component of the pioneering Manchester University MkI digital computer. Because it enabled both data and program instructions to be stored in the computer, it was soon used worldwide in the development of the early stored-program computers.[br]Principal Honours and DistinctionsKnighted 1976. OBE 1945. CBE 1961. FRS 1950. Hon. DSc Durham 1964, Sussex 1971, Wales 1971. First Royal Society of Arts Benjamin Franklin Medal 1957. City of Philadelphia John Scott Award 1960. Royal Society Hughes Medal 1963. Institution of Electrical Engineers Faraday Medal 1972. Institute of Electrical and Electronics Engineers Pioneer Award 1973.BibliographyWilliams contributed papers to many scientific journals, including Proceedings of the Royal Society, Proceedings of the Cambridge Philosophical Society, Journal of the Institution of Electrical Engineers, Proceedings of the Institution of Mechanical Engineers, Wireless Engineer, Post Office Electrical Engineers' Journal. Note especially: 1948, with J.Kilburn, "Electronic digital computers", Nature 162:487; 1949, with J.Kilburn, "A storage system for use with binary digital computing machines", Proceedings of the Institution of Electrical Engineers 96:81; 1975, "Early computers at Manchester University", Radio \& Electronic Engineer 45:327. Williams also collaborated in the writing of vols 19 and 20 of the MIT RadiationLaboratory Series.Further ReadingB.Randell, 1973, The Origins of Digital Computers, Berlin: Springer-Verlag. M.R.Williams, 1985, A History of Computing Technology, London: Prentice-Hall. See also: Stibitz, George R.; Strachey, Christopher.KFBiographical history of technology > Williams, Sir Frederic Calland
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8 ASDEC
automatic selection of digital electronic computers - система автоматического выбора цифровой вычислительной машины -
9 Artificial Intelligence
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)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)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, EventuallyJust 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 ProgramMany 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)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)[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)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 FormThe 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)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)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)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)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 FormationIt 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)We might distinguish among four kinds of 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.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.... 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)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 ContextsEven 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)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)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 IntelligenceThe 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)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 PropositionsIn 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)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)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)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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10 computer
= cmpr1) компьютера) вычислительная машина, ВМб) электронная вычислительная машина, ЭВМ2) вычислительное устройство, вычислитель•- analog computer
- analog-digital computer - asynchronous computer
- AT-compatible computer
- automatic computer
- azimuth rate computer
- beam-steering computer
- bearing distance computer
- board computer
- briefcase computer
- bubble-domain computer
- buffered computer
- business computer
- client computer
- clipboard computer
- coherent optical computer
- communication computer
- complex instruction set computer
- control computer
- course-line computer
- cryogenic computer - dead-reckoning computer
- dedicated computer
- desktop computer
- digital computer
- discontinued computer
- diskless computer
- dockable computer
- docked computer
- electronic digital computer
- embedded personal computer
- fifth generation computer
- first generation computer
- fixed-program computer
- flight computer
- flight-path computer
- fluid computer
- fluid-jet computer
- follow-on computer
- fourth generation computer
- fuzzy computer
- general-purpose computer
- green computer
- guest computer
- guidance computer
- guidance and navigation computer
- hand-held personal computer
- high-end computer
- home computer
- host computer
- hybrid computer
- IBM-compatible computer
- industrial computer
- interface computer
- keyboard computer
- keyboardless computer
- laptop computer
- legacy-free computer
- logarithmic computer
- mainframe computer
- massively parallel computer
- master computer
- member computer
- memory test computer
- microfluidic computer
- microprogrammable computer
- mobile computer
- mobile network computer
- multiaccess computer
- multihomed computer
- multimedia personal computer
- multi-user computer
- navigation computer
- network computer
- nonsequential computer
- notebook computer
- object computer
- office computer
- off-line computer
- offset-course computer
- on-board computer
- one-address computer
- on-hand wearable personal computer
- on-line computer
- optical computer
- palmtop personal computer
- parallel computer
- parallel course computer
- parallel digital computer
- Pel computer
- pen computer
- pen-based computer
- performance optimized with enhanced RISC personal computer
- peripheral computer
- personal computer
- pipelined computer
- plugboard computer
- pocket computer
- pocket personal computer
- pocket-size personal computer
- portable computer
- process computer
- process control computer
- quantum computer
- radiac computer
- range computer
- reduced instruction set computer
- remote computer
- rho-theta computer
- ruggedized computer
- satellite computer
- scientific computer
- second generation computer
- sequential computer
- serial computer
- serial digital computer
- simultaneous computer
- single-board computer
- single-chip computer
- slave computer
- small business computer
- solid-state computer
- sonar data computer
- source computer
- special-purpose computer
- stack-oriented computer
- standalone computer
- stored-program computer
- superconducting computer
- supervisory computer
- synchronous computer
- synergetic computer
- talking computer
- tandem computers
- target intercept computer
- tesselated computer
- third generation computer
- three-address computer
- Total Talk computer
- tse computer
- ultralight computer
- undocked computer
- universal computer
- wired-program computer
- zero wait state computer -
11 computer
1) компьютера) вычислительная машина, ВМб) электронная вычислительная машина, ЭВМ2) вычислительное устройство, вычислитель•- analog computer
- analog-digital computer
- Apple Macintosh computer
- arbitrary course computer
- asynchronous computer
- AT-compatible computer
- automatic computer
- azimuth rate computer
- beam-steering computer
- bearing distance computer
- board computer
- briefcase computer
- bubble-domain computer
- buffered computer
- business computer
- client computer
- clipboard computer
- coherent optical computer
- communication computer
- complex instruction set computer
- control computer
- course-line computer
- cryogenic computer
- data analog computer
- database computer
- dead-reckoning computer
- dedicated computer
- desktop computer
- digital computer
- discontinued computer
- diskless computer
- dockable computer
- docked computer
- electronic digital computer
- embedded personal computer
- fifth generation computer
- first generation computer
- fixed-program computer
- flight computer
- flight-path computer
- fluid computer
- fluid-jet computer
- follow-on computer
- fourth generation computer
- fuzzy computer
- general-purpose computer
- green computer
- guest computer
- guidance and navigation computer
- guidance computer
- hand-held personal computer
- high-end computer
- home computer
- host computer
- hybrid computer
- IBM-compatible computer
- industrial computer
- interface computer
- keyboard computer
- keyboardless computer
- laptop computer
- legacy-free computer
- logarithmic computer
- mainframe computer
- massively parallel computer
- master computer
- member computer
- memory test computer
- microfluidic computer
- microprogrammable computer
- mobile computer
- mobile network computer
- multiaccess computer
- multihomed computer
- multimedia personal computer
- multi-user computer
- navigation computer
- network computer
- nonsequential computer
- notebook computer
- object computer
- office computer
- off-line computer
- offset-course computer
- on-board computer
- one-address computer
- on-hand wearable personal computer
- on-line computer
- optical computer
- palmtop personal computer
- parallel computer
- parallel course computer
- parallel digital computer
- Pel computer
- pen computer
- pen-based computer
- performance optimized with enhanced RISC personal computer
- peripheral computer
- personal computer
- pipelined computer
- plugboard computer
- pocket computer
- pocket personal computer
- pocket-size personal computer
- portable computer
- process computer
- process control computer
- quantum computer
- radiac computer
- range computer
- reduced instruction set computer
- remote computer
- rho-theta computer
- ruggedized computer
- satellite computer
- scientific computer
- second generation computer
- sequential computer
- serial computer
- serial digital computer
- simultaneous computer
- single-board computer
- single-chip computer
- slave computer
- small business computer
- solid-state computer
- sonar data computer
- source computer
- special-purpose computer
- stack-oriented computer
- standalone computer
- stored-program computer
- superconducting computer
- supervisory computer
- synchronous computer
- synergetic computer
- talking computer
- tandem computers
- target intercept computer
- tesselated computer
- third generation computer
- three-address computer
- Total Talk computer
- tse computer
- ultralight computer
- undocked computer
- universal computer
- wired-program computer
- zero wait state computerThe New English-Russian Dictionary of Radio-electronics > computer
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12 арифмометр
1) General subject: adding machine, arithmometer, calculating-machine, calculator, calculating machine2) Computers: number cruncher3) Engineering: adder4) Economy: comptometer5) Information technology: arithmetic device6) Cartography: automatic desk computer, desk calculating machine, digital computer, digital counter7) Geophysics: number crunching8) Advertising: desk calculator, desk-top calculator9) Makarov: desk computing machine -
13 ASDEC
1) Военный термин: applied systems development and evaluation center -
14 перфолента
1) General subject: digital tape, scotch tape3) Engineering: paper tape, perforated tape, punched tape, sprocket tape, sprocketed tape, tape4) Cinema: computer tape5) Polygraphy: (бумажная) paper tape6) Telecommunications: automatic send-receive, paper type7) Automation: punch tape8) Telegraphy: chad tape, send-receive9) Makarov: perforator tape, tape medium -
15 система автоматического выбора цифровой вычислительной машины
Engineering: automatic selection of digital electronic computersУниверсальный русско-английский словарь > система автоматического выбора цифровой вычислительной машины
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16 generation
1) создание, образование, формирование, генерация2) генерирование; порождение3) поколение (напр., компьютеров)4) матем. (функциональное) преобразование•- algorithmic pattern generation
- allophone string generation
- automatic character generation
- code generation
- data generation
- design generation
- digital-pattern generation
- entity generation
- fault generation
- function generation
- generation of computers
- generation of information
- noise generation
- parity generation
- picture generation
- random variate generation
- report generation
- schematicgeneration
- specification-driven software generation
- square-root generation
- stimuli generation
- symbol generation
- system generation
- test generation
- test-vector generation
- token generation
- verification condition generation
- wait-state generationEnglish-Russian dictionary of computer science and programming > generation
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Automatic link establishment — Automatic Link Establishment, commonly known as ALE, is the worldwide de facto standard for digitally initiating and sustaining HF (High Frequency) radio communications.cite web|title=Frequency Agile Systems in the MF/HF Bands |author=Telecom… … Wikipedia
Automatic control — is the research area and theoretical base for mechanization and automation, employing methods from mathematics and engineering. A central concept is that of the system which is to be controlled, such as a rudder, propeller or an entire ballistic… … Wikipedia
Digital video recorder — Foxtel iQ, a combined digital video recorder and satellite receiver. V+, a combined digital vid … Wikipedia
Digital electronics — Main articles: Electronics and Electronic circuit Digital electronics represent signals by discrete bands of analog levels, rather than by a continuous range. All levels within a band represent the same signal state. Relatively small changes to… … Wikipedia
Digital photography — Nikon D700 a 12.1 megapixel full frame DSLR … Wikipedia
