DocumentCode :
2985697
Title :
Stochastic stability of adaptive quantizers for Markov sources
Author :
Yüksel, Serdar
Author_Institution :
Dept. of Math. & Stat., Queen´´s Univ., Kingston, ON, Canada
fYear :
2009
fDate :
June 28 2009-July 3 2009
Firstpage :
527
Lastpage :
531
Abstract :
A stochastic stability result for a class of adaptive quantizers which were introduced by Goodman and Gersho is presented. We consider a case where the input process is a linear Markov source which is not necessarily stable. We present a stochastic stability result for the estimation error and the quantizer, thus generalizing the stability result of Goodman and Gersho to a Markovian, and furthermore to an unstable, setting. Furthermore, it is shown that, there exists a unique invariant distribution for the state and the quantizer parameters under mild irreducibility conditions. The second moment under the invariant distribution is finite, if the system noise is Gaussian.
Keywords :
Gaussian noise; Markov processes; linear systems; quantisation (signal); stability; Gaussian noise; adaptive quantizer; estimation error; linear Markov source; stochastic stability; Bismuth; Estimation error; Gaussian noise; Mathematics; Probability distribution; Random variables; Stability; Statistics; Stochastic processes; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Theory, 2009. ISIT 2009. IEEE International Symposium on
Conference_Location :
Seoul
Print_ISBN :
978-1-4244-4312-3
Electronic_ISBN :
978-1-4244-4313-0
Type :
conf
DOI :
10.1109/ISIT.2009.5205725
Filename :
5205725
Link To Document :
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