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Books > Professional & Technical > Energy technology & engineering > Electrical engineering
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Neural Information Processing and VLSI (Paperback, Softcover reprint of the original 1st ed. 1995)
Loot Price: R4,546
Discovery Miles 45 460
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Neural Information Processing and VLSI (Paperback, Softcover reprint of the original 1st ed. 1995)
Series: The Springer International Series in Engineering and Computer Science, 304
Expected to ship within 10 - 15 working days
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Neural Information Processing and VLSI provides a unified treatment
of this important subject for use in classrooms, industry, and
research laboratories, in order to develop advanced artificial and
biologically-inspired neural networks using compact analog and
digital VLSI parallel processing techniques. Neural Information
Processing and VLSI systematically presents various neural network
paradigms, computing architectures, and the associated
electronic/optical implementations using efficient VLSI design
methodologies. Conventional digital machines cannot perform
computationally-intensive tasks with satisfactory performance in
such areas as intelligent perception, including visual and auditory
signal processing, recognition, understanding, and logical
reasoning (where the human being and even a small living animal can
do a superb job). Recent research advances in artificial and
biological neural networks have established an important foundation
for high-performance information processing with more efficient use
of computing resources. The secret lies in the design optimization
at various levels of computing and communication of intelligent
machines. Each neural network system consists of massively
paralleled and distributed signal processors with every processor
performing very simple operations, thus consuming little power.
Large computational capabilities of these systems in the range of
some hundred giga to several tera operations per second are derived
from collectively parallel processing and efficient data routing,
through well-structured interconnection networks. Deep-submicron
very large-scale integration (VLSI) technologies can integrate tens
of millions of transistors in a single silicon chip for complex
signal processing and information manipulation. The book is
suitable for those interested in efficient neurocomputing as well
as those curious about neural network system applications. It has
been especially prepared for use as a text for advanced
undergraduate and first year graduate students, and is an excellent
reference book for researchers and scientists working in the fields
covered.
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