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Discrete Neural Computation : A Theoretical Foundation - Kai-Yeung Siu

Discrete Neural Computation

A Theoretical Foundation


Published: 28th January 1995
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Written by the three leading authorities in the field, this book brings together -- in one volume -- the recent developments in discrete neural computation, with a focus on neural networks with discrete inputs and outputs. It integrates a variety of important ideas and analytical techniques, and establishes a theoretical foundation for discrete neural computation. Discusses the basic models for discrete neural computation and the fundamental concepts in computational complexity; establishes efficient designs of threshold circuits for computing various functions; develops techniques for analyzing the computational power of neural models. A reference/text for computer scientists and researchers involved with neural computation and related disciplines.

Linear Threshold Element
Computing Symmetric Functions
Depth Efficient Arithmetic Circuits
Depth-Size Tradeoffs
Computing with Small Weights
Rational Approximation and Optimal Size Circuits
Geometric Framework and Spectral Analysis
Limitations of AND-OR Circuits
Lower Bounds via Communication Complexity
Hopfield Network
Table of Contents provided by Publisher. All Rights Reserved.

ISBN: 9780133007084
ISBN-10: 0133007081
Series: Prentice Hall Information and System Sciences
Audience: Tertiary; University or College
Format: Paperback
Language: English
Number Of Pages: 432
Published: 28th January 1995
Publisher: Pearson Education (US)
Country of Publication: US
Dimensions (cm): 24.0 x 18.5  x 2.0
Weight (kg): 0.82
Edition Number: 1