Learning on Silicon - Adaptive VLSI Neural Systems (Hardcover, 1999 ed.)

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 in unpredictable environments through mechanisms of adaptation and learning. 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.

General

Imprint:	Springer
Country of origin:	Netherlands
Series:	The Springer International Series in Engineering and Computer Science, 512
Release date:	June 1999
First published:	1999
Editors:	G. Cauwenberghs • Magdy A. Bayoumi
Dimensions:	235 x 155 x 25mm (L x W x T)
Format:	Hardcover
Pages:	426
Edition:	1999 ed.
ISBN-13:	978-0-7923-8555-4
Categories:	Books > Computing & IT > General theory of computing > General Books > Computing & IT > Applications of computing > General Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > General
LSN:	0-7923-8555-1
Barcode:	9780792385554

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