In this paper, a new and fast encoding algorthm for vector quantization is presenfed. This algorithm makes fall use of two characterisstics of a vector: the sum and the variance. A vector is separated into two subvectors: one is composed of the first half of vector components and the other consists of the remaining vector components. Three inequalities based on the sums and varances of a vector and Its two subyectors components are introduced to rejict those codewords that are impossible to be the nearest code-word, thereby saving a great deal of computational time, while in-troducing no estra distortion compared to the conventional full search algorithm. The simulation results show that the proposed algorithm is faster than the equal-average nearest neighbor search (ENNS), the improved ENNS, the equal-average equal-varlance nearest neighbor search (EENNS)and the improved EENNS algo-rithms. Comparing with the improved EENNS algorithm, the pro-posed algorithm reduces the computational time and the number of distortion calculations by 2.4% to 6%and 20.5% to 26.8%. re-spectively The average improvements of the computational time and the number of distortion calculations are 4% and 24.6% for the codebook sizes of 128 to 1024, respectively.