Fast clustering algorithm for vector quantisation

A fast clustering algorithm is presented as an alternative to the K-means algorithm. By encoding training vectors selectively and changing the codebook updating step, the algorithm reduces the computation time. Simulations show that the algorithm outperforms the K-means algorithm in computation time and performance in terms of mean-squared-error