Title :
Comparison of Class 1 and Class 2 frequency domain matrix and vector estimation filters with adaptive FIR filters
Author :
Duysal, Erkan ; Lindquist, Claude S.
Author_Institution :
Dept. of Electr. & Comput. Eng., Miami Univ., Coral Gables, FL, USA
Abstract :
Class 1 and 2 frequency domain block matrix and vector estimation filters are compared with adaptive FIR (finite impulse response) filters based on gradient search algorithms, including Newton, steepest descent, and LMS (least mean square). It is shown that the algorithm of the Class 1 filter considered has the same form as the Wiener-Hopf equation. It is found that the Class 2 estimation filter has the form of an adaptive FIR filter based on Newton´s method. Simulations show that utilizing smoothing techniques can further improve the performance and efficiency of the Class 2 estimation filter
Keywords :
adaptive filters; digital filters; filtering and prediction theory; frequency-domain analysis; matrix algebra; vectors; Class 1 filter; Class 2 estimation filter; LMS; Newton´s method; Wiener-Hopf equation; adaptive FIR filters; efficiency; finite impulse response; frequency domain block matrix; gradient search algorithms; least mean square; performance; smoothing techniques; steepest descent; vector estimation filters; Adaptive filters; Equations; Finite impulse response filter; Frequency domain analysis; Frequency estimation; Information filtering; Information filters; Iterative algorithms; Smoothing methods; Wiener filter;
Conference_Titel :
Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-2470-1
DOI :
10.1109/ACSSC.1991.186534
