Self-Organization and Associative Memory
Başlık:
Self-Organization and Associative Memory
ISBN:
9783642881633
Personal Author:
Edition:
3rd ed. 1989.
Yayın Bilgileri:
Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1989.
Fiziksel Tanımlama:
XV, 312 p. 100 illus. online resource.
Series:
Springer Series in Information Sciences ; 8
Contents:
1. Various Aspects of Memory -- 1.1 On the Purpose and Nature of Biological Memory -- 1.2 Questions Concerning the Fundamental Mechanisms of Memory -- 1.3 Elementary Operations Implemented by Associative Memory -- 1.4 More Abstract Aspects of Memory -- 2. Pattern Mathematics -- 2.1 Mathematical Notations and Methods -- 2.2 Distance Measures for Patterns -- 3. Classical Learning Systems -- 3.1 The Adaptive Linear Element (Adaline) -- 3.2 The Perceptron -- 3.3 The Learning Matrix -- 3.4 Physical Realization of Adaptive Weights -- 4. A New Approach to Adaptive Filters -- 4.1 Survey of Some Necessary Functions -- 4.2 On the "Transfer Function" of the Neuron -- 4.3 Models for Basic Adaptive Units -- 4.4 Adaptive Feedback Networks -- 5. Self-Organizing Feature Maps -- 5.1 On the Feature Maps of the Brain -- 5.2 Formation of Localized Responses by Lateral Feedback -- 5.3 Computational Simplification of the Process -- 5.4 Demonstrations of Simple Topology-Preserving Mappings -- 5.5 Tonotopic Map -- 5.6 Formation of Hierarchical Representations -- 5.7 Mathematical Treatment of Self-Organization -- 5.8 Automatic Selection of Feature Dimensions -- 6. Optimal Associative Mappings -- 6.1 Transfer Function of an Associative Network -- 6.2 Autoassociative Recall as an Orthogonal Projection -- 6.3 The Novelty Filter -- 6.4 Autoassociative Encoding -- 6.5 Optimal Associative Mappings -- 6.6 Relationship Between Associative Mapping, Linear Regression, and Linear Estimation -- 6.7 Recursive Computation of the Optimal Associative Mapping -- 6.8 Special Cases -- 7. Pattern Recognition -- 7.1 Discriminant Functions -- 7.2 Statistical Formulation of Pattern Classification -- 7.3 Comparison Methods -- 7.4 The Subspace Methods of Classification -- 7.5 Learning Vector Quantization -- 7.6 Feature Extraction -- 7.7 Clustering -- 7.8 Structural Pattern Recognition Methods -- 8. More About Biological Memory -- 8.1 Physiological Foundations of Memory -- 8.2 The Unified Cortical Memory Model -- 8.3 Collateral Reading -- 9. Notes on Neural Computing -- 9.1 First Theoretical Views of Neural Networks -- 9.2 Motives for the Neural Computing Research -- 9.3 What Could the Purpose of the Neural Networks be? -- 9.4 Definitions of Artificial "Neural Computing" and General Notes on Neural Modelling -- 9.5 Are the Biological Neural Functions Localized or Distributed? -- 9.6 Is Nonlinearity Essential to Neural Computing? -- 9.7 Characteristic Differences Between Neural and Digital Computers -- 9.8 "Connectionist Models" -- 9.9 How can the Neural Computers be Programmed? -- 10. Optical Associative Memories -- 10.1 Nonholographic Methods -- 10.2 General Aspects of Holographic Memories -- 10.3 A Simple Principle of Holographic Associative Memory -- 10.4 Addressing in Holographic Memories -- 10.5 Recent Advances of Optical Associative Memories -- Bibliography on Pattern Recognition -- References.
Abstract:
While the present edition is bibliographically the third one of Vol. 8 of the Springer Series in Information Sciences (IS 8), the book actually stems from Vol. 17 of the series Communication and Cybernetics (CC 17), entitled Associative Memory - A System-Theoretical Approach, which appeared in 1977. That book was the first monograph on distributed associative memories, or "content-addressable memories" as they are frequently called, especially in neural-networks research. This author, however, would like to reserve the term "content-addressable memory" for certain more traditional constructs, the memory locations of which are selected by parallel search. Such devices are discussed in Vol. 1 of the Springer Series in Information Sciences, Content-Addressable Memories. This third edition of IS 8 is rather similar to the second one. Two new discussions have been added: one to the end of Chap. 5, and the other (the L VQ 2 algorithm) to the end of Chap. 7. Moreover, the convergence proof in Sect. 5.7.2 has been revised.
Ek Kurum Yazarı:
Dil:
English