Title :
Robust Quantization of ε-Contaminated Data
Author :
Poor, H. Vincent
Author_Institution :
Univ. of Illinois, Urbana, IL, USA
fDate :
3/1/1985 12:00:00 AM
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;
Journal_Title :
Communications, IEEE Transactions on
DOI :
10.1109/TCOM.1985.1096271