Introduction to Neural Networks

Name: Introduction to Neural Networks
Price: 6.12 USD
Availability: InStock
ISBN: 9780262510813

ISBN-10: 0262510812

ISBN-13: 9780262510813

Edition: 1995

Authors: James A. Anderson

List price: $75.00

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Description:

An Introduction to Neural Networks falls into a new ecological niche for texts. Based on notes that have been class-tested for more than a decade, it is aimed at cognitive science and neuroscience students who need to understand brain function in terms of computational modeling, and at engineers who want to go beyond formal algorithms to applications and computing strategies. It is the only current text to approach networks from a broad neuroscience and cognitive science perspective, with an emphasis on the biology and psychology behind the assumptions of the models, as well as on what the models might be used for. It describes the mathematical and computational tools needed and provides an…

Book details

List price: $75.00
Copyright year: 1995
Publisher: MIT Press
Publication date: 3/16/1995
Binding: Paperback
Pages: 666
Size: 7.50" wide x 9.25" long x 1.75" tall
Weight: 3.080
Language: English

James A. Anderson is Professor in the Department of Cognitive and Linguistic Sciences at Brown University.



Introduction


Acknowledgements


Properties of Single Neurons


Synaptic Integration and Neuron Models


Essential Vector Operations


Lateral Inhibition and Sensory Processing


Simple Matrix Operations


The Linear Associator: Background and Foundations


The Kinear Associator: Simulations


Early Network Models: The Perceptron


Gradient Descent Algorithms


Representation of Information


Applications of Simple Associators: Concept Formation and Object Motion


Energy and Neural Networks: Hopfield Networks and Boltzmann Machines


Nearest Neighbor Models


Adaptive Maps


The BSB Model: A Simple Nonlinear Autoassociative Neural Network


Associative Computation


Teaching Arithmetic to a Neural Network


Afterword


Index