A block quasi-Newton algorithm implemented in the frequency domain

Author

Berberidis, Kostas ; Palicot, Jacques

Author_Institution

Computer Technol. Inst., Patras, Greece

Volume

3

fYear

1996

fDate

7-10 May 1996

Firstpage

1731

Abstract

A new block adaptive filtering algorithm is derived. The algorithm belongs to the quasi-Newton class of algorithms which are known to have superior convergence properties as compared to gradient algorithms. An important feature of the algorithm is that it lends itself to efficient implementation in the frequency domain. The computational complexity of the frequency domain version of the algorithm is comparable to that of the self-orthogonalizing frequency domain block LMS algorithm while it converges at a faster rate. Depending on the input signal this improvement in performance may be significant in some practical cases

Keywords

Newton method; adaptive filters; adaptive signal processing; computational complexity; convergence of numerical methods; filtering theory; frequency-domain synthesis; least mean squares methods; block adaptive filtering algorithm; block quasiNewton algorithm; computational complexity; convergence properties; frequency domain block LMS algorithm; frequency domain implementation; gradient algorithms; input signal; performance improvement; self-orthogonalizing algorithm; Adaptive filters; Adaptive signal processing; Computational complexity; Convergence; Electronic mail; Filtering algorithms; Frequency domain analysis; Least squares approximation; Nonlinear filters; Signal processing algorithms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on

Conference_Location

Atlanta, GA

ISSN

1520-6149

Print_ISBN

0-7803-3192-3

Type

conf

DOI

10.1109/ICASSP.1996.544142

Filename

544142