Title :
The application of Volterra series to signal estimation
Author :
Morrison, Ian J. ; Rayner, Peter J W
Author_Institution :
Dept. of Eng., Cambridge Univ., UK
Abstract :
The authors examine the problem of estimating signals corrupted by additive non-Gaussian noise. Since the linear filter is known to be optimal if the noise is Gaussian, they apply general nonlinear filters, based on Volterra series, to the non-Gaussian case. Nonlinear Wiener filters are derived, and their performance investigated in example non-Gaussian noise densities
Keywords :
filtering and prediction theory; noise; series (mathematics); signal processing; Volterra series; Wiener filters; additive nonGaussian noise; nonGaussian noise densities; nonlinear filters; performance; signal estimation; Additive noise; Convolution; Estimation; Finite impulse response filter; Gaussian noise; Integrated circuit noise; Nonlinear filters; Power measurement; Vectors; Wiener filter;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-0003-3
DOI :
10.1109/ICASSP.1991.150725
