A non-metrical space search algorithm for fast Gaussian vector quantization

Three algorithms to speed up full covariance multivariate Gaussian vector quantizers are presented. The speed-up is achieved by avoiding the distance calculation for a considerable number of codebook classes at each input frame. In two cases, this pruning is guided by thresholds U/sub kappa lambda / which are computed for each class pair in a preprocessing stage. The computation of the U/sub kappa lambda /s from the codebook parameters by the gradient projection method leads to an admissible search strategy. Two of the proposed search procedures trace accuracy for speed. Both of them allow more than fivefold speed-up vector quantization at very low frame error rates, and without any degradation of word accuracy.<>