Signal processing filters under modeling uncertainties
Abstract
Matched and Wiener filters are considered for signal processing applications when the a priori information about signal and noise characteristics are not completely specified. The approach is to design filters which are saddle-point or max-min solutions for the criterion functional (mean-squared-error or signal-to-noise ratio) over the classes of allowable signal shapes and signal and noise spectral densities. Two-dimensional discrete-parameter processes are considered, and some numerical examples are presented.
- Publication:
-
Interim Report Pennsylvania Univ
- Pub Date:
- December 1979
- Bibcode:
- 1979penn.rept.....K
- Keywords:
-
- Mathematical Models;
- Signal Processing;
- Signal To Noise Ratios;
- Wiener Filtering;
- Flux Density;
- Noise Spectra;
- Power Spectra;
- Electronics and Electrical Engineering