Elimination criteria based on mean value

variance and norm was often used in the VQ encoding to reject unlikely codewords.However

these elimination criteria have obvious computational redundancy.A new elimination criteria based on triangular inequality in subspace was proposed.By finding the optimal reference point of distance computation

the new elimination criteria can reject more unlikely codewords than other elimination criteria using variance and norm.The elimination criteria based on variance can be seen as the special case of new elimination criteria.Before the search process

all codewords in the codebook are Hadamard-transformed and sorted in the ascending order of their first elements.During the search process

the mean value of a vector was used to terminate the search process

and the new elimination criteria based on triangular inequality in subspace was applied to reject most unlikely codewords.Experiments results demonstrate that the performance of the proposed algorithm is much better than other nearest neighbor codeword search algorithms.Compared with the Hadamard-Transformed based Equal-Average Equal-variance Equal-norm Nearest Neighbor Search algorithm

the proposed algorithm reduces the computational time by 8% to 26%.