벡터 양자화를 위한 학습 알고리즘을 이용한 음성 전송 기술에 관한 연구

A study on the competitive learning algorithm for robust vector qantization to transmit speech signal

The efficient representation and encoding of signals with limited resources, e.g., finite storage capacity and restricted transmission bandwidth, is a fundamental problem in technical information processing systems. Typically under realistic circumstances, the encoding and communication of message has to deal with different sources of noise and disturbances. In this paper, I propose a unifying approach to data compression by robust vector quantization, which explicitly deals with channel noise, and random elimination of prototypes. The resulting algorithm is able to limit the detrimental effect of noise in a very general communication scenario. In this paper, based on the robust vector quantization I have an experiment about speech coding.