Adaptive analog VLSI neural systems by M. A. Jabri

Cover of: Adaptive analog VLSI neural systems | M. A. Jabri

Published by Chapman & Hall in London, New York .

Written in English

Read online

Subjects:

  • Integrated circuits -- Very large scale integration.,
  • Neural networks (Computer science)

Edition Notes

Includes bibliographical references (p. [249]-257) and index.

Book details

StatementM.A. Jabri, R.J. Coggins and B.G. Flower.
ContributionsCoggins, R. J., Flower, B. G.
Classifications
LC ClassificationsQA76.87 .J3 1996x
The Physical Object
Paginationvii, 262 p. :
Number of Pages262
ID Numbers
Open LibraryOL20083997M
ISBN 100412616300

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The approach is systems and applications oriented. Learning on Silicon: Adaptive VLSI Neural Systems Volume of The Springer International Series in Engineering and Computer Science: Editors: G. Home Browse by Title Books Analog VLSI and neural systems. Analog VLSI and () Efficient Mixed-Signal Neurocomputing Via Successive Integration and Rescaling, IEEE Transactions on Very Large Scale Integration (VLSI) Systems Schemmel J and Schwartz M A VLSI implementation of the adaptive exponential integrate-and-fire neuron model.

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Learning on Silicon combines models of adaptive information processing in the brain with advances in microelectronics technology and circuit design. The premise is to construct integrated systems not only loaded with sufficient computational power to handle demanding signal processing tasks in sensory perception and pattern recognition, but also capable of operating autonomously and robustly.

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