Title :
A new signal estimation algorithm for use in Wiener filtering
Author :
Lindquist, Claude S. ; Powell, Clinton C.
Author_Institution :
Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA
Abstract :
A nonlinear smoothing algorithm is presented for determining signal autocorrelation and power spectral density matrices. The algorithm can be utilized to generate matrix filters. It is used to form a Wiener estimation filter. Simulations are presented to confirm the usefulness of the smoothing algorithm and to suggest a time-varying memoryless filter approach
Keywords :
computerised signal processing; digital filters; digital simulation; estimation theory; filtering and prediction theory; signal detection; smoothing circuits; Wiener estimation filter; Wiener filtering; matrix filters; nonlinear smoothing algorithm; power spectral density matrices; signal autocorrelation; signal estimation algorithm; time-varying memoryless filter; Autocorrelation; Ear; Estimation; Filtering algorithms; Frequency domain analysis; Noise reduction; Smoothing methods; Stochastic resonance; Wiener filter;
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
DOI :
10.1109/ISCAS.1990.112232
