Neuromorphic Systems Engineering Neural Networks in Silicon /

Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic syste...

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Bibliographic Details
Corporate Author: SpringerLink (Online service)
Other Authors: Lande, Tor Sverre. (Editor)
Format: Electronic
Language:English
Published: Boston, MA : Springer US, 1998.
Series:The Springer International Series in Engineering and Computer Science, Analog Circuits and Signal Processing, 447
Subjects:
Online Access:View fulltext via EzAccess
Description
Summary:Neuromorphic Systems Engineering: Neural Networks in Silicon emphasizes three important aspects of this exciting new research field. The term neuromorphic expresses relations to computational models found in biological neural systems, which are used as inspiration for building large electronic systems in silicon. By adequate engineering, these silicon systems are made useful to mankind. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the reader with a snapshot of neuromorphic engineering today. It is organized into five parts viewing state-of-the-art developments within neuromorphic engineering from different perspectives. Neuromorphic Systems Engineering: Neural Networks in Silicon provides the first collection of neuromorphic systems descriptions with firm foundations in silicon. Topics presented include: large scale analog systems in silicon neuromorphic silicon auditory (ear) and vision (eye) systems in silicon learning and adaptation in silicon merging biology and technology micropower analog circuit design analog memory analog interchipcommunication on digital buses £/LIST£ Neuromorphic Systems Engineering: Neural Networks in Silicon serves as an excellent resource for scientists, researchers and engineers in this emerging field, and may also be used as a text for advanced courses on the subject.
Physical Description:XVII, 462 p. online resource.
ISBN:9780585280011
ISSN:0893-3405 ;