DocumentCode :
1026760
Title :
Parallel architecture for prototype training
Author :
Zhu, Mingda ; Loh, N. ; Khalaf, S. ; Siy, P.
Author_Institution :
Oakland University, Center for Robotics & Advanced Automation, Rochester, USA
Volume :
22
Issue :
21
fYear :
1986
Firstpage :
1100
Lastpage :
1102
Abstract :
The letter suggests an efficient parallel hardware architecture for prototype training in pattern recognition. Sample means and covariance matrices are computed by the same architecture and much attention is paid to the implementation of covariance matrices. A k2-chip of processor elements is used to implement covariance matrices.
Keywords :
computerised pattern recognition; parallel architectures; covariance matrices; k2-chip; parallel hardware architecture; pattern recognition; processor elements; prototype training;
fLanguage :
English
Journal_Title :
Electronics Letters
Publisher :
iet
ISSN :
0013-5194
Type :
jour
DOI :
10.1049/el:19860754
Filename :
4256968
Link To Document :
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