Overview

This text provides a unified treatment of this subject for use in classrooms, industry and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analogue and digital VLSI parallel processing techniques. The book presents various neural network paradigms, computing architectures and the associated electronic/optical implementations using efficient VLSI design methodologies. Conventional digital machines cannot perform computationally-intensive tasks with satisfactory performance in such areas as intelligent perception, including visual and auditory signal processing, recognition, understanding and logical reasoning (where the human being and even a small living animal can do a superb job). Recent research advances in artificial and biological neural networks have established an important foundation for high-performance information processing with more efficient use of computing resources.

Full Product Details

Author:   Bing J. Sheu ,  Joongho Choi
Publisher:   Springer
Imprint:   Springer
Edition:   1995 ed.
Volume:   304
Dimensions:   Width: 15.50cm , Height: 3.10cm , Length: 23.50cm
Weight:   2.170kg
ISBN:  

9780792395478

ISBN 10:   0792395476
Pages:   559
Publication Date:   28 February 1995
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

I Paradigms and Models.- 1 Introduction.- 2 Artificial Neural Network Algorithms.- 3 Other Computational Intelligence Topics.- 4 Biologically-Inspired Vision Processing.- 5 Cellular Neural Networks.- 6 Paralleled Hardware Annealing for Optimal Solutions.- II VLSI Design Technology.- 7 Design Methodologies of VLSI Neural Networks.- 8 Analog VLSI Building Blocks.- 9 Digital VLSI Neuroprocessors.- III Applications and System Prototyping.- 10 Back-Propagation Neural Networks.- 11 Self-Organization Neural Networks.- 12 Advanced Vision Chips and Systems.- 13 Photonic Neural Networks.- 14 Smart-Pixel, Cellular Neural Network, and Chaotic Chips.- 15 Various Subsystem and System Construction Examples.- 16 Selected Commercial Products From Industry.- References.

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