DocumentCode
756080
Title
Neural-style microsystems that learn
Author
Alspector, Joshua
Author_Institution
Bellcore, Red Bank, NJ, USA
Volume
27
Issue
11
fYear
1989
Firstpage
29
Lastpage
36
Abstract
The basic operation of biological and electronic (artificial) neural networks (NNs) is examined. Learning by NNs is discussed, covering supervised learning, particularly back-propagation, and unsupervised and reinforcement learning. The use of VLSI implementation to speed learning is considered briefly. Applications of neural-style learning chips to pattern recognition, data compression, optimization, and expert systems is discussed. Problem areas and issues for further research are addressed.<>
Keywords
VLSI; digital signal processing chips; learning systems; neural nets; VLSI; back-propagation; data compression; expert systems; learning; neural networks; neural-style learning chips; optimization; pattern recognition; Artificial neural networks; Data compression; Expert systems; Pattern recognition; Supervised learning; Very large scale integration;
fLanguage
English
Journal_Title
Communications Magazine, IEEE
Publisher
ieee
ISSN
0163-6804
Type
jour
DOI
10.1109/35.41398
Filename
41398
Link To Document