Acceleration of the LBG algorithm
A concentric spherical search technique is proposed to speed up the clustering process in VQ design. A linear data structure is incorporated into the LBG algorithm to keep and update the information about the proximity among the codewords. This proximity information can significantly reduce the number of candidate codewords to be the closest to a given training vector. An improved k-means type VQ design algorithm is proposed based on the new search technique and the supporting data structure. The new algorithm is simple to implement, valid for general error metric, and demonstrated by present experiments to be considerably faster than previous algorithms. >