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perceptron learning rule

См. также в других словарях:

  • 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

  • Delta rule — The delta rule is a gradient descent learning rule for updating the weights of the artificial neurons in a single layer perceptron. It is a special case of the more general backpropagation algorithm. For a neuron with activation function the… …   Wikipedia

  • Neural network — For other uses, see Neural network (disambiguation). Simplified view of a feedforward artificial neural network The term neural network was traditionally used to refer to a network or circuit of biological neurons.[1] The modern usage of the term …   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

  • Connectionism — is a set of approaches in the fields of artificial intelligence, cognitive psychology, cognitive science, neuroscience and philosophy of mind, that models mental or behavioral phenomena as the emergent processes of interconnected networks of… …   Wikipedia

  • Recurrent neural network — A recurrent neural network (RNN) is a class of neural network where connections between units form a directed cycle. This creates an internal state of the network which allows it to exhibit dynamic temporal behavior.Recurrent neural networks must …   Wikipedia

  • Artificial neural network — An artificial neural network (ANN), usually called neural network (NN), is a mathematical model or computational model that is inspired by the structure and/or functional aspects of biological neural networks. A neural network consists of an… …   Wikipedia

  • ADALINE — (Adaptive Linear Neuron or later Adaptive Linear Element) is a single layer neural network. It was developed by Professor Bernard Widrow and his graduate student Ted Hoff at Stanford University in 1960. It is based on the McCulloch Pitts neuron.… …   Wikipedia

  • Neuroph — Stable release 2.5RC1 / April 17, 2011; 5 months ago (2011 04 17) Written in Java Platform Java platform …   Wikipedia

  • Réseau de neurones artificiels —  Pour l’article homonyme, voir Réseau de neurones (biologie).  Pour les articles homonymes, voir Réseau. Un réseau de neurones artificiels est un modèle de calcul dont la conception est très schématiquement inspirée du fonctionnement… …   Wikipédia en Français

  • AI winter — See also and An AI Winter is a collapse in the perception of artificial intelligence research. The term was coined by analogy with the relentless spiral of a nuclear winter: a chain reaction of pessimism in the AI community, followed by pessimism …   Wikipedia

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