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

fYear

1991

fDate

4-6 Nov 1991

Firstpage

678

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 1991. 1991 Conference Record of the Twenty-Fifth Asilomar Conference on

Conference_Location

Pacific Grove, CA

ISSN

1058-6393

Print_ISBN

0-8186-2470-1

Type

conf

DOI

10.1109/ACSSC.1991.186534

Filename

186534