Using models of biological systems as springboards to a broad range of applications, this volume presents the basic ideas of neural networks in mathematical form. Comprehensive in scope, Neural Network Principles outlines the structure of the human brain, explains the physics of neurons, derives the standard neuron state equations, and presents the consequences of these mathematical models. Author Robert L. Harvey derives a set of simple networks that can filter, recall, switch, amplify, and recognize input signals that are all patterns of neuron activation. The author also discusses properties of general interconnected neuron groups, including the well-known Hopfield and perception neural networks using a unified approach along with suggestions of new design procedures for both. He then applies the theory to synthesize artificial neural networks for specialized tasks. In addition, Neural Network Principles outlines the design of machine vision systems, explores motor control of the human brain and presents two examples of artificial hand-eye systems, demonstrates how to solve large systems of interconnected neurons, and considers control and modulation in the human brain-mind with insights for a new understanding of many mental illnesses.
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This volume presents the basic ideas of neural networks (theory and design principles) in mathematical form--using models of biological systems as springboards to a broad range of applications.
"About this title" may belong to another edition of this title.
Book Description Prentice Hall, 1994. Hardcover. Book Condition: New. 1st. Bookseller Inventory # DADAX0130633305
Book Description Book Condition: Brand New. Book Condition: Brand New. Bookseller Inventory # 97801306333091.0