Neural Network Modeling: Statistical Mechanics and Cybernetic Perspectives, 1st Edition (Hardback) book cover

Neural Network Modeling

Statistical Mechanics and Cybernetic Perspectives, 1st Edition

By P. S. Neelakanta, Dolores DeGroff

CRC Press

256 pages

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Hardback: 9780849324888
pub: 1994-07-12
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Description

Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.

Table of Contents

Introduction

Neural and Brain Complex

Concepts of Mathematical Neurobiology

Pseudo-Thermodynamics of Neural Activity

The Physics of Neural Activity: A Statistical Mechanics Perspective

Stochastic Dynamics of the Neural Complex

Neural Field Theory: Quasiparticle Dynamics and Wave Mechanics Analogies of Neural Networks

Informatic Aspects of Neurocybernetics

Appendices: Magnetism and the Ising Spin-Glass Model

Matrix Methods in Little's Model

Overlap of Replicas and Replica Symmetry

Bibliography

Index

Subject Categories

BISAC Subject Codes/Headings:
COM051240
COMPUTERS / Software Development & Engineering / Systems Analysis & Design
TEC008000
TECHNOLOGY & ENGINEERING / Electronics / General