Research Catalog

Title

Digital neural networks / S.Y. Kung.

Author

Kung, S. Y. (Sun Yuan)

Publication

Englewood Cliffs, N.J. : PTR Prentice Hall, [1993], ©1993.

Items in the Library & Off-site

Holdings

Details

Description

xviii, 444 pages : illustrations; 25 cm.

Series Statement

Prentice-Hall information and system sciences series

Uniform Title

Prentice-Hall information and system sciences series.

Subjects

• Neural networks (Computer science)
• Artificial intelligence

Bibliography (note)

• Includes bibliographical references (p. 413-434) and index.

Contents

• Pt. I. Introduction. 1. Overview. 1.2. Applications, Algorithms, and Architectures. 1.3. Taxonomy of Neural Networks -- Pt. II. Unsupervised Models. 2. Fixed-Weight Associative Memory Networks. 2.2. Feedforward Associative Memory Networks. 2.3. Feedback Associative Memory Networks. 3. Competitive Learning Networks. 3.2. Basic Competitive Learning Networks. 3.3. Adaptive Clustering Techniques: VQ and ART. 3.4. Self-Organizing Feature Map: Sensitivity to Neighborhood and History. 3.5. Neocognition: Hierarchically Structured Model -- Pt. III. Supervised Models. 4. Decision-Based Neural Networks. 4.2. Linear Perceptron Networks. 4.3. Decision-Based Neural Networks. 4.4. Applications to Signal/Image Classifications. 5. Approximation/Optimization Neural Networks. 5.2. Linear Approximation Networks. 5.3. Nonlinear Multilayer Back-Propagation Networks. 5.4. Training Versus Generalization Performance. 5.5. Applications of Back-Propagation Networks --
• Pt. IV. Temporal Models. 6. Deterministic Temporal Neural Networks. 6.2. Linear Temporal Dynamic Models. 6.3. Nonlinear Temporal Dynamic Models. 6.4. Prediction-Based Temporal Networks. 7. Stochastic Temporal Networks: Hidden Markov Models. 7.2. From Markov Model to Hidden Markov Model. 7.3. Learning Phase of Hidden Markov Models. 7.4. Retrieving Phase of Hidden Markov Models. 7.5. Applications to Speech, ECG, and Character Recognition -- Pt. V. Advanced Topics. 8. Principal Component Neural Networks. 8.2. From Wiener Filtering to PCA. 8.3. Symmetric Principal Component Analysis. 8.4. BP Network for Asymmetric PCA Problems. 8.5. Applications to Signal/Image Processing. 9. Stochastic Annealing Networks for Optimization. 9.2. Stochastic Neural Networks. 9.3. Applications to Combinatorial Optimization and Image Restoration. 9.4. Boltzmann Machine -- Pt. VI. Implementation. 10. Architecture and Implementation. 10.2. Mapping Neural Nets to Array Architectures.
• 10.3. Dedicated Neural Processing Circuits. 10.4. General-Purpose Digital Neurocomputers.

ISBN

0136123260

LCCN

92042737

OCLC

ocm27066578

Owning Institutions

Columbia University Libraries