edited by David Zhang (Hong Kong Polytechnic University, Hong Kong) & Sankar K Pal (The Indian Statistical Institute, Calcutta, India)

About the Editors

David Zhang is founder and editor-in-chief of International Journal of Image and Graphics, and an associate editor for IEEE Trans. On Systems, Man and Cybernetics, Pattern Recognition, International Journal of Pattern Recognition and Artificial Intelligence, International Journal of Robotics and Automation, and Neural, Parallel and Scientific Computations. He has published over 170 papers including six books.
 

Sandar K Pal has won many awards, including 1990 S S Bhatnagar Prize (most coveted award for a scientist in India), 1993 NASA Tech Brief Award, 1994 IEEE Trans. Neural Networks Outstanding Paper Award, and FICCI-2001 Award in Engineering and Technology, among others. He is also the co-author/co-editor of nine books and of about 300 research publications.
 

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.

• 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 Pérez 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 Alarcón)
• 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 Martínez 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)