Robust techniques for signal processing - A survey

Mathematics

Scientific paper

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Linear Filters, Matched Filters, Minimax Technique, Reliability Engineering, Robustness (Mathematics), Signal Processing, Data Smoothing, Network Synthesis, Noise Spectra, Parameter Identification, Signal Detection, Statistical Analysis

Scientific paper

A survey which focuses on minimax robust signal-processing schemes is examined. Although key results of other robust statistical procedures are considered, the emphasis is on the contributions made in robust signal processing. It is shown that robustness formulations take two basic forms: robustness with respect to uncertain second-order statistical properties (spectral properties) of signals of noise and robustness with respect to uncertainty in the marginal distribution of the noise or signal process. In the first case, the robust methods take the form of linear procedures, whereas in the second case, nonlinear procedures are used. Consideration is given to robust linear filters for signal estimation, to robust linear filters for signal detection and related applications, to nonlinear methods for robust signal detection, to nonlinear methods for robust estimation, and to robust data quantization. The interrelationships among many of the results are also discussed in the survey.

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