Circuit implementation of K-winner machine

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.