
000 | 00766camuuu200253 a 4500 | |
001 | 000000097201 | |
005 | 19980603112333.0 | |
008 | 930104s1993 njua b 001 0 eng | |
010 | ▼a 93000026 | |
015 | ▼a GB93-40838 | |
020 | ▼a 0133689034 | |
040 | ▼a DLC ▼c DLC ▼d UKM | |
049 | 1 | ▼l 121003454 ▼f 과학 |
050 | 0 0 | ▼a QA76.87 ▼b .C45 1993 |
082 | 0 0 | ▼a 006.3 ▼2 20 |
090 | ▼a 006.3 ▼b C525n | |
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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No. 1 | Location Sejong Academic Information Center/Science & Technology/ | Call Number 006.3 C525n | Accession No. 151019825 | Availability Available | 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