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
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;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19860754