DocumentCode :
775477
Title :
Robust Quantization of ε-Contaminated Data
Author :
Poor, H. Vincent
Author_Institution :
Univ. of Illinois, Urbana, IL, USA
Volume :
33
Issue :
3
fYear :
1985
fDate :
3/1/1985 12:00:00 AM
Firstpage :
218
Lastpage :
222
Abstract :
The problem of robust quantization of data with uncertain statistical properties is considered. Uncertainty in the statistics of the data is modeled by assuming that the data have a probability density function of the ε-contaminated form, and a minimax approach to robust design is adopted. An approximation is developed for the asymptotic worst-case distortion (over the ε-contaminated class) produced by an arbitrary companded quantizer, and the quantizer design which minimizes this worst-case distortion is derived. The robustness of the resulting design is verified numerically for the particular problem of quantizing ε-contaminated Gaussian data.
Keywords :
Data communications; Quantization; Game theory; Minimax techniques; Performance analysis; Probability density function; Quantization; Robustness; Signal design; Signal processing; Statistics; Uncertainty;
fLanguage :
English
Journal_Title :
Communications, IEEE Transactions on
Publisher :
ieee
ISSN :
0090-6778
Type :
jour
DOI :
10.1109/TCOM.1985.1096271
Filename :
1096271
Link To Document :
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