DocumentCode :
766655
Title :
Vector Quantizers and Predictive Quantizers for Gauss-Markov Sources
Author :
Gray, Robert M. ; Linde, Yoseph
Author_Institution :
Stanford Univ., Stanford, CA, USA
Volume :
30
Issue :
2
fYear :
1982
fDate :
2/1/1982 12:00:00 AM
Firstpage :
381
Lastpage :
389
Abstract :
Low-rate vector quantizers are designed and simulated for highly correlated Gauss-Markov sources and the resulting performance is compared with Arnstein´s optimized predictive quantizer and with Huang and Schultheiss´ optimized transform coder. Two implementations of vector quantizers are considered: full search vector quantizers-which are optimal but require large codebook searches-and tree searched vector quantizers-which are suboptimal but require far less searching. The various systems are compared on the basis of performance, complexity, and generality of design techniques.
Keywords :
Markov processes; Prediction methods; Quantization (signal); Signal quantization; Transform coding; Communication standards; Data compression; Degradation; Design optimization; Gaussian processes; Information theory; Predictive models; Quantization; Reliability theory; Welding;
fLanguage :
English
Journal_Title :
Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
0090-6778
Type :
jour
DOI :
10.1109/TCOM.1982.1095471
Filename :
1095471
Link To Document :
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