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Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 512)
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About this book
This edited volume covers the spectrum of Learning on Silicon in five parts: adaptive sensory systems, neuromorphic learning, learning architectures, learning dynamics, and learning systems. The 18 chapters are documented with examples of fabricated systems, experimental results from silicon, and integrated applications ranging from adaptive optics to biomedical instrumentation.
As the first comprehensive treatment on the subject, Learning on Silicon serves as a reference for beginners and experienced researchers alike. It provides excellent material for an advanced course, and a source of inspiration for continued research towards building intelligent adaptive machines.
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A.G. Andreou, Johns Hopkins University
Editors and Affiliations
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John Hopkins University Dept. Electrical & Computer Engineering, Baltimore, USA
G. Cauwenberghs
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University of Southwestern Louisiana Center for Advanced Computer Studies, Lafayette, USA
Magdy A. Bayoumi
Bibliographic Information
Book Title: Learning on Silicon
Book Subtitle: Adaptive VLSI Neural Systems
Editors: G. Cauwenberghs, Magdy A. Bayoumi
Series Title: The Springer International Series in Engineering and Computer Science
Publisher: Springer New York, NY
Copyright Information: Springer-Verlag US 1999
Hardcover ISBN: 978-0-7923-8555-4Published: 30 June 1999
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XVI, 426