Parallel VLSI neural system design
Author(s)
Bibliographic Information
Parallel VLSI neural system design
Springer, c1999
Available at 7 libraries
Note
Includes bibliographical references (p. [235]-252) and index
Description and Table of Contents
Description
An integrated design approach to ANNs for pattern recognition applications, investigating three topics of the system design methodology, including several model definitions, architectural descriptions and hardware implementations. Following an overview, engineering applications of ANNs to fuzzy clustering, speech recognition, classification and pattern recognition are covered. Aimed at researchers and graduate engineers working in the area of VLSI circuit and system design, as well as for reference on senior undergraduate level courses on parallel neural computing and VLSI system applications, David Zhangs book will prove useful to understanding this new and exciting discipline.
Table of Contents
VLSI Neural System Design Methodology.- PART I: PARALLEL ANN MODELS: An Unsupervised Learning Model. A Supervised Training Model. A Neural-like Network Model.- PART II: VLSI ARCHITECTURES: Mapping ANN onto Systolic Arrays. A Parallel Architecture Implemented by Systolic Arrays. A pipelined Architecture based on Window Operation. A Simplified Architecture Using A Priori Knowledge.- PART III: HARDWARE IMPLEMENTATION: Computational Blocks Design for Digital ANN. Digital ANN Compressor Design. Hybrid Programmable ANN Design. VLSI Implementation for Finite Ring ANN. Conclusions and Prospects.- Bibliography.- Index.
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