Hadamard transform based equal-average equal-variance equal-norm nearest neighbor codeword search algorithm

The paper presents a novel, efficient, nearest-neighbor codeword search algorithm based on three elimination criteria in the Hadamard transform (HT) domain. 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, we first perform the HT on the input vector and calculate its variance and norm, and secondly exploit three efficient elimination criteria to find the nearest codeword to the input vector using the up-down search mechanism near the initial best-match codeword. Experimental results demonstrate that the performance of the proposed algorithm is much better than that of most existing nearest neighbor codeword search algorithms, especially in the case of high dimension