A Tabu Search Based Maximum Descent Algorithm for VQ Codebook Design

摘要

A maximum descent (MD) method has been proposed for vector quantization (VQ) codebook design. Compared with the traditional generalized Lloyd algorithm (GLA), the MD algorithm achieves better codebook performance with far less computation time. However, searching for the optimal partitioning hyperplane of a multidimensional cluster Is a difficult problem in the MD algorithm. Three partition techniques have been pro- Posed for the MD method in the literature.