Brainware: Bio-inspired Architecture And Its Hardware Implementation
Will be published approx. on 19. February 2001
Book
Hardback
244 pages
978-981-02-4547-4 (ISBN)
Description
The human brain, the ultimate intelligent processor, can handle ambiguous and uncertain information adequately. The implementation of such a human-brain architecture and function is called "brainware". Brainware is a candidate for the new tool that will realize a human-friendly computer society. As one of the LSI implementations of brainware, a "bio-inspired" hardware system is discussed in this book.Consisting of eight enriched versions of papers selected from IIZUKA '98, this volume provides wide coverage, from neuronal function devices to vision systems, chaotic systems, and also an effective design methodology of hierarchical large-scale neural systems inspired by neuroscience. It can serve as a reference for graduate students and researchers working in the field of brainware. It is also a source of inspiration for research towards the realization of a silicon brain.
More details
Series
Language
English
Place of publication
Singapore
Singapore
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
ISBN-13
978-981-02-4547-4 (9789810245474)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Person
Content
Neuron MOS Transistor: The Concept and Its Application (T Shibata); Adaptive Learning Neuron Integrated Circuits Using Ferroelectric-Gate FETs (S-M Yoon et al.); An Analog-Digital Merged Circuit Architecture Using PWM Techniques for Bio-Inspired Nonlinear Dynamical Systems (T Morie et al.); Application-Driven Design of Bio-Inspired Low-Power Vision Circuits and Systems (A Konig et al.); Motion Detection with Bio-Inspired Analog MOS Circuits (H Yonezu et al.); v MOS Cellular-Automaton Circuit for Picture Processing (M Ikebe & Y Amemiya); Semiconductor Chaos-Generating Elements of Simple Structure and Their Integration (K Hoh et al.); Computation in Single Neuron with Dendritic Trees (N Katayama et al.).