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