An introduction to neural networks

An introduction to neural networks / James A. Anderson.

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Bibliographic Details
Main Author:	Anderson, James A.
Corporate Authors:	CogNet, CogNet Library
Format:	eBook
Language:	English
Published:	Cambridge, Mass. : MIT Press, ©1995. ©1995
Series:	Bradford Book Ser.
Subjects:	Neural networks (Neurobiology) Neural networks (Computer science) simulation.
Online Access:	Click for online access

Table of Contents:

Introduction
1. Properties of single neurons
2. Synaptic integration and neuron models
3. Essential vector operations
4. Lateral inhibition and sensory processing
5. Simple matrix operations
6. The linear associator : background and foundations
7. The Kinear associator : simulations
8. Early network models : the Perceptron
9. Gradient descent algorithms
10. Representation of information
11. Applications of simple associators : concept formation and object motion
12. Energy and neural networks : Hopfield networks and Boltzmann machines
13. Nearest neighbor models
14. Adaptive maps
15. The BSB model : a simple nonlinear autoassociative neural network
16. Associative Computation
17. Teaching Arithmetic to a Neural Network
Afterword.