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input-to-hidden weights

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  • Neural cryptography — is a branch of cryptography dedicated to analyzing the application of stochastic algorithms, especially neural network algorithms, for use in encryption and cryptanalysis. Contents 1 Definition 2 Applications 3 Neural key e …   Wikipedia

  • Backpropagation — Backpropagation, or propagation of error, is a common method of teaching artificial neural networks how to perform a given task. It was first described by Paul Werbos in 1974, but it wasn t until 1986, through the work of David E. Rumelhart,… …   Wikipedia

  • connectionism — /keuh nek sheuh niz euhm/, n. Psychol. the theory that all mental processes can be described as the operation of inherited or acquired bonds between stimulus and response. [CONNECTION + ISM] * * * In cognitive science, an approach that proposes… …   Universalium

  • Radial basis function network — A radial basis function network is an artificial neural network that uses radial basis functions as activation functions. They are used in function approximation, time series prediction, and control.Network architectureRadial basis function (RBF) …   Wikipedia

  • Perceptron — Perceptrons redirects here. For the book of that title, see Perceptrons (book). The perceptron is a type of artificial neural network invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt.[1] It can be seen as the simplest… …   Wikipedia

  • Multilayer perceptron — A multilayer perceptron (MLP) is a feedforward artificial neural network model that maps sets of input data onto a set of appropriate output. An MLP consists of multiple layers of nodes in a directed graph, with each layer fully connected to the… …   Wikipedia

  • Clique problem — The brute force algorithm finds a 4 clique in this 7 vertex graph (the complement of the 7 vertex path graph) by systematically checking all C(7,4)=35 4 vertex subgraphs for completeness. In computer science, the clique problem refers to any of… …   Wikipedia

  • Kalman filter — Roles of the variables in the Kalman filter. (Larger image here) In statistics, the Kalman filter is a mathematical method named after Rudolf E. Kálmán. Its purpose is to use measurements observed over time, containing noise (random variations)… …   Wikipedia

  • Feedforward neural network — A feedforward neural network is an artificial neural network where connections between the units do not form a directed cycle. This is different from recurrent neural networks.The feedforward neural network was the first and arguably simplest… …   Wikipedia

  • Economic Affairs — ▪ 2006 Introduction In 2005 rising U.S. deficits, tight monetary policies, and higher oil prices triggered by hurricane damage in the Gulf of Mexico were moderating influences on the world economy and on U.S. stock markets, but some other… …   Universalium

  • Counterpropagation network — The counterpropagation network is a hybrid network. It consists of an outstar network and a competitive filter network. It was developed in 1986 by Robert Hecht Nielsen. It is guaranteed to find the correct weights, unlike regular back… …   Wikipedia

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