Neural networks and systolic array design

Bibliographic Information

Neural networks and systolic array design

editors, David Zhang, Sankar K. Pal

(Series in machine perception and artificial intelligence / editors, H. Bunke, P.S.P. Wang, v. 49)

World Scientific, c1992

Available at  / 3 libraries

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Note

Includes bibliographical references and index

Description and Table of Contents

Description

Neural networks (NNs) and systolic arrays (SAs) have many similar features. This volume describes, in a unified way, the basic concepts, theories and characteristic features of integrating or formulating different facets of NNs and SAs, as well as presents recent developments and significant applications. The articles, written by experts from all over the world, demonstrate the various ways this integration can be made to efficiently design methodologies, algorithms and architectures, and also implementations, for NN applications. 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 networks, and vision.

Table of Contents

  • Neural Networks and Systolic Arrays: Models and Integration (D Zhang & S K Pal)
  • Systolic Array Methodology for a Neural Model to Solve the Mixture Problem (R M Perez et al.)
  • Morphological Endmember Identification and Its Systolic Array Design (P L Aguilar et al.)
  • MANTRA I: A Systolic Array for Neural Computation (M A Viredaz & P Ienne)
  • Mixed-Signal Neuro-Fuzzy Processor Implementations: Sequential Architectures and Circuit-Level Description (J Madrenas & E Alarcon)
  • CMAC Neural Networks and Systolic Implementation (B D Liu et al.)
  • Quadrant Interlocking Factorization on Systolic and Wavefront Array Processors (M P Bekakos et al.)
  • Systolic S.O.M. Neural Network for Hyperspectral Image Classification (P Martinez et al.)
  • Optimizing and Learning Algorithm for Feedforward Neural Networks and Its Implementation by Systolic Array (P B Burgos)
  • Parallel ANN Architecture for Fuzzy Patterns (D Zhang & S K Pal)
  • Pipelined Systolic Arrays for Time-Delay Neural Networks (D Zhang & S K Pal)
  • An Integrated Intelligent Classification Engine (I2CE) for Biosignal Engineering (A N Kastania & M P Bekakos)
  • Multiplierless Designs for Artificial Neural Networks (H K Kwan)
  • A VLSI System for Intelligent Decision Making a Real-Time (N Ranganathan & M I Patel)
  • Reconfigurable Hardware Systolic Array for Real-Time Compartmental Modeling of Large-Scale Artificial Nervous Systems (M Korkin)
  • Implementing and Mapping ANNs on Reconfigurable Mesh Massively Parallel Architectures (W N Li & J J Jenq).

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Details

  • NCID
    BA60584424
  • ISBN
    • 9810248407
  • Country Code
    us
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    New Jersey
  • Pages/Volumes
    xiv, 405 p.
  • Size
    24 cm
  • Parent Bibliography ID
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