## Neural Computing - An IntroductionNeural computing is one of the most interesting and rapidly growing areas of research, attracting researchers from a wide variety of scientific disciplines. Starting from the basics, Neural Computing covers all the major approaches, putting each in perspective in terms of their capabilities, advantages, and disadvantages. The book also highlights the applications of each approach and explores the relationships among models developed and between the brain and its function. A comprehensive and comprehensible introduction to the subject, this book is ideal for undergraduates in computer science, physicists, communications engineers, workers involved in artificial intelligence, biologists, psychologists, and physiologists. |

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adaptive ART network associative memory autoassociative basic basis functions behaviour best-match binary biological Boltzmann machine brain Chapter class pattern classification complex connected content-addressable memory control-1 convergence correct output decision boundary define delta rule dendrite distance distributed energy function energy landscape error function Euclidean example exemplar feature map feedforward generalisation gradient descent Grossberg Hamming distance hidden units Hopfield net Hopfield network implementation Initialise input layer input pattern input vector Kohonen learning algorithm learning rule linear linear classifier mathematical matrix means minima multilayer perceptron neighbourhood neural computing neural networks neuron non-linear output layer output unit parallel pattern recognition pattern space perform phase phonemes produce random recognition layer represents response self-organising shown in figure signal simple solution supervised learning techniques temperature term thresholding function tion training cycle training data training set tuple vigilance threshold visualise weight values weight vector weighted sum whilst winning node XOR problem zero

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Page 242 - Neural networks are computer models based on the operation of components of the brain. They demonstrate some of the features of intelligent behaviour and are capable of learning.

### References to this book

Bounded Rationality in Macroeconomics: The Arne Ryde Memorial Lectures Thomas J. Sargent No preview available - 1993 |

Connectionist Speech Recognition: A Hybrid Approach Hervé A. Bourlard,Nelson Morgan Limited preview - 1994 |