Neural network approaches to fast and low rate vector quantization

In this paper, two codebook search methods and a coding scheme are proposed for fast and low rate vector quantization using the self-organizing feature maps (SOFM). Based on the topology preservation property of the SOFM, the search methods use the distance between adjacent input vectors to guide the codebook search process and to determine searching sequence of codevectors. The novel coding scheme, which can be considered as a vector version of delta modulation, eliminates the correlation buried in the source sequence and hence reduces the rate. Simulation results demonstrate the effectiveness of proposed methods and better performances than those obtained previously