Title :
Circuit implementation of K-winner machine
Author :
Ridella, S. ; Rovetta, S. ; Zunino, R.
Author_Institution :
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
fDate :
7/8/1999 12:00:00 AM
Abstract :
The K-winner machine (KWM) model for supervised classification enhances vector quantisation by characterising classification outcomes with confidence levels. Each data-space location is assigned a specific local bound to the error probability. Structural simplicity makes the implementation compatible with circuitry for classical VQ, and features high speed and efficiency
Keywords :
error statistics; learning (artificial intelligence); neural nets; pattern classification; vector quantisation; K-winner machine; KWM model; classification outcomes; confidence levels; data-space location; efficiency; error probability; specific local bound; speed; supervised classification; vector quantisation;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:19990820
