DocumentCode
1978353
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
fYear
1991
fDate
14-17 Apr 1991
Firstpage
1481
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location
Toronto, Ont.
ISSN
1520-6149
Print_ISBN
0-7803-0003-3
Type
conf
DOI
10.1109/ICASSP.1991.150725
Filename
150725
Link To Document