A three state fast vector quantization algorithm based on code vector activity detection

This paper introduces a novel method for reducing the number of distance calculations in the generalized Lloyd algorithm (GLA), which is a widely used method to construct a codebook in vector quantization. Reduced comparison search detects the activity of the code vectors and utilizes it with the activity history to classify the training vectors into three groups static codevectors, permanent static codevectors and active codevector. For training vectors whose current code vector has not been modified for K successive iterations, we consider this codevector reach its optimal position in space. We remove the stabilized codevector and its data vectors from the training process. For training vectors whose current code vector has not been modified for less than K iterations, we calculate distances only to the active code vectors. Large proportion of the distance calculations can be omitted without significantly sacrificing the optimality of the partition.</p