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
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