Vector quantization by neural network
Yu Ting He, Qianren Zhang, Yizheng Ye, Zhongrong Li · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1990
Vector quantization has been widely used in image encoding systems and speech recognition systems science 1980's. In this paper, three kinds of vector quantization approaches are introduced, which are based on neural networks. The principles of using neural networks to improve the performance of vector quantization are described. Because of high parallel computation, learning function, high fault tolerance and selforganizing capability of neural networks, the performance of vector quantizers is improved.