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Neural networks : a tutorial

Neural networks : a tutorial (Loan 24 times)

Material type
단행본
Personal Author
Chester, Michael.
Title Statement
Neural networks : a tutorial / Michael Chester.
Publication, Distribution, etc
Englewood Cliffs, N.J. :   PTR Prentice Hall,   c1993.  
Physical Medium
viii, 182 p. : ill. ; 24 cm.
ISBN
0133689034
Bibliography, Etc. Note
Includes bibliographical references (p. 171-179) and index.
Subject Added Entry-Topical Term
Neural networks (Computer science).
비통제주제어
Computers, Networks,,
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049 1 ▼l 121003454 ▼f 과학
050 0 0 ▼a QA76.87 ▼b .C45 1993
082 0 0 ▼a 006.3 ▼2 20
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100 1 ▼a Chester, Michael.
245 1 0 ▼a Neural networks : ▼b a tutorial / ▼c Michael Chester.
260 ▼a Englewood Cliffs, N.J. : ▼b PTR Prentice Hall, ▼c c1993.
300 ▼a viii, 182 p. : ▼b ill. ; ▼c 24 cm.
504 ▼a Includes bibliographical references (p. 171-179) and index.
650 0 ▼a Neural networks (Computer science).
653 0 ▼a Computers ▼a Networks

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No. Location Call Number Accession No. Availability Due Date Make a Reservation Service
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Contents information

Table of Contents


CONTENTS
Preface = vi
Acknowledgements = viii
1 Structure of an Artificial Neural Network = 1
 Artificial Neurons = 1
 Taxonomies = 6
 Neural Network Logic = 11
2 Applications = 12
 Robots = 16
 Implementations = 17
3 The Early Years = 19
 The Perceptron = 19
 The LMS Law = 26
4 The Hopfield Net = 28
 Symbolic Operations = 31
 Network Capacity and False Exemplars = 33
 The Lyapunov Condition = 34
 A Continuous Model = 35
 Hopfield Network Applications = 37
5 Self-Organizing Maps = 42
 Applications of the Self-Organizing Map = 45
 Other Studies of Topological Mapping = 47
 A Note on "Selecting a Winner" = 48
6 Backpropagation = 50
 Error Surface = 51
 Generalized Delta Rule = 53
 Synaptic Changes in Hidden Layers = 56
 Backpropagation Summary = 57
 A Hyperplane Model = 57
 A Neural Speech Synthesizer = 59
 Other Applications = 61
 Limitations and Remedies = 62
 Recurrent Backpropagation = 63
7 Learning Laws and Continued Taxonomy = 66
 Learning Laws = 67
 Unsupervised Learning Laws = 68
8 Adaptive Resonance = 71
 The ART Paradigms = 75
 A Note on Parsimony = 81
9 Bidirectional Associative Memory = 82
 TAM = 86
 MAM = 86
 ABAM = 87
 The Noise-Saturation Dilemma = 89
 ABAM: Implementation = 90
 CABAM = 91
 RABAM = 92
10 Variations on Neural Themes = 95
 The Boltzmann Machine, a Probabilistic Model = 95
 The Hamming Network = 98
 Brain-State-in-a-Box(BSB) = 101
 The Neocognitron = 103
 Restricted Coulomb Energy = 107
 Dystal, a Biological Model = 114
 Drive Reinforcement Model = 117
11 Fuzzy Theroy = 119
 Functions of Fuzzy Vectors = 120
 Fuzziness versus Aristotle = 122
 A Fuzzy Neural Underwater Sound Detector = 125
 A Fuzzy Truck Driver = 130
12 Integrated Circuits = 135
 Building Block and Thin-Film Approaches = 136
 Adaptive Synapses Based on MNOS and CCD Technologies = 137
 An All-Digital Neural Network = 140
 A Silicon Retina = 145
13 Optical Neural Nets = 148
 Optical Techniques = 149
 Holograms = 150
14 The Evolution of Intelligence = 155
 Genetics = 155
 Modular Neural Evolution = 158
 Natural Selection = 159
 Simulated Imagination = 162
Appendix: Mathematical Notation = 167
References and Bibligraphy = 171
Index = 180


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