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Parallel VLSI neural system design by David Zhang

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Published by Springer in Singapore, New York .
Written in English


  • Neural networks (Computer science),
  • Parallel processing (Electronic computers),
  • Integrated circuits -- Very large scale integration

Book details:

Edition Notes

Includes bibliographical references (p. [235]-252) and index.

StatementDavid Zhang.
LC ClassificationsQA76.87 .Z473 1999
The Physical Object
Paginationxiii, 257 p. :
Number of Pages257
ID Numbers
Open LibraryOL379647M
ISBN 109813083301
LC Control Number98041790

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Research and development of new computer architectures and VLSI circuits for neural networks and artificial intelligence have been increased in order to meet the new performance requirements. This book presents novel approaches and trends on VLSI implementations of machines for these applications.   In this chapter we describe the design of a VLSI system for intelligent decision making in real time. The system architecture is an integration of a learning system (an Artificial Neural Network), and a rule based fuzzy expert system implemented as linear systolic arrays. This introductory book is not only for the novice reader, but for experts in a variety of areas including parallel computing, neural network computing, computer science, communications, graph 3/5(1). Neural Information Processing and VLSI provides a unified treatment of this important subject for use in classrooms, industry, and research laboratories, in order to develop advanced artificial and biologically-inspired neural networks using compact analog and digital VLSI parallel processing techniques.

This book brings together in one place important contributions and state-of-the-art research in the rapidly advancing area of analog VLSI neural networks. The book serves as an excellent reference, providing insights into some of the most important issues in analog VLSI neural networks research efforts. Welcome to NCTU Parallel Computing System Lab (PCS Lab). Our research focuses on design and implementation of parallel computing systems. The expertize of the group spans across multiple design layers, including multi-core architecture, parallel task management, parallel applications, system optimization, design framework, and methodology. Design and Fabrication of VLSI Components for a General Purpose Analog Neural Computer Paul Mueller, Jan van der Spiegel, David Blackman, Timothy Chiu, Thomas Clare, Christopher Donham et al. Pages A Chip that Focuses an Image on Itself. So far, he has published more than papers and seven books, including Parallel Computer System Designs for Image Processing & Pattern Recognition (HIT, ), Parallel VLSI Neural System Design (Springer, ), Automated Biometrics: Technologies and Systems (Kluwer Academic, ), Data Management and Internet Computing for Image/Pattern.

  This book explores the theory, design and implementation of analog VLSI circuits, inspired by visual motion processing in biological neural networks. Using a novel approach pioneered by the author himself, Stocker explains in detail the construction of a series of electronic chips, providing the reader with a valuable practical insight into the. A new approach for the design of two-dimensional (2-D) finite-impulse response (FIR) linear-phase digital filters was presented based on a parallel neural networks algorithm (PNNA) by analyzing.   The research of the VLSI Information Processing (VIP) group is at the intersection of wireless communication, digital signal processing (DSP), and very-large-scale integration (VLSI) circuit and system design. The book will be useful to graduate students and researchers in many related areas, not only as a reference book but also as a textbook for some parts of the curriculum. It will also benefit researchers and practitioners in industry and R&D laboratories who are working in the fields of system design, VLSI, parallel processing, neural.