VLSI Artificial Neural Networks Engineering

✍ Scribed by Waleed Fakhr, Mohamed I. Elmasry (auth.), Mohamed I. Elmasry (eds.)

Publisher: Springer US
Year: 1994
Tongue: English
Leaves: 334
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Engineers have long been fascinated by how efficient and how fast biological neural networks are capable of performing such complex tasks as recognition. Such networks are capable of recognizing input data from any of the five senses with the necessary accuracy and speed to allow living creatures to survive. Machines which perform such complex tasks as recognition, with similar ac curacy and speed, were difficult to implement until the technological advances of VLSI circuits and systems in the late 1980's. Since then, the field of VLSI Artificial Neural Networks (ANNs) have witnessed an exponential growth and a new engineering discipline was born. Today, many engineering curriculums have included a course or more on the subject at the graduate or senior under graduate levels. Since the pioneering book by Carver Mead; "Analog VLSI and Neural Sys tems", Addison-Wesley, 1989; there were a number of excellent text and ref erence books on the subject, each dealing with one or two topics. This book attempts to present an integrated approach of a single research team to VLSI ANNs Engineering.

✦ Table of Contents

Front Matter....Pages i-xv
An Overview....Pages 1-31
A Sampled-Data CMOS VLSI Implementation of a Multi-Character ANN Recognition System....Pages 33-89
A Design Automation Environment for Mixed Analog/Digital ANNs....Pages 91-137
A Compact VLSI Implementation of Neural Networks....Pages 139-156
An All-Digital VLSI ANN....Pages 157-189
A Neural Predictive Hidden Markov Model Architecture for Speech and Speaker Recognition....Pages 191-245
Minimum Complexity Neural Networks for Classification....Pages 247-282
A Parallel ANN Architecture for Fuzzy Clustering....Pages 283-302
A Pipelined ANN Architecture for Speech Recognition....Pages 303-321
Back Matter....Pages 323-329

✦ Subjects

Circuits and Systems;Electrical Engineering;Statistical Physics, Dynamical Systems and Complexity

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