Title :
Predictive VQ for noisy channel spectrum coding: AR or MA?
Author :
Skoglund, Jan ; Lindén, Jan
Author_Institution :
Dept. of Inf. Theory, Chalmers Univ. of Technol., Goteborg, Sweden
Abstract :
In this paper, the performance of different predictive vector quantization (PVQ) structures is studied and compared for different degrees of channel noise. Predictive quantization schemes with an auto-regressive (AR) decoder structure are compared with schemes that employ a moving average (MA) decoder. For noisy channels MA prediction performs better than AR. It is shown here that a combination of a PVQ scheme (AR or MA) and a memoryless VQ outperforms both types of traditional predictive quantizer schemes in noiseless as well as noisy channels
Keywords :
autoregressive processes; channel coding; decoding; moving average processes; noise; prediction theory; speech coding; telecommunication channels; vector quantisation; AR; MA; auto-regressive decoder structure; channel noise; memoryless VQ; moving average decoder; noisy channel spectrum coding; performance; predictive VQ; speech coding; Decoding; Information theory; Robustness; Speech coding; Vector quantization;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.596197