Hirschman Optimal Transform Block LMS Adaptive Filter

Author

Alkhouli, O. ; DeBrunner, V.E.

Author_Institution

Sch. of Elec. & Comp. Eng., Oklahoma Univ., Norman, OK, USA

Volume

3

fYear

2007

fDate

15-20 April 2007

Abstract

In this paper, we derive a "convolution theorem" suitable for the Hirschman optimal transform (HOT), a unitary transform derived from a discrete-time, discrete-frequency version of the entropy-based uncertainty measure first described by Hirschman (1957). We use the result to develop a fast block-LMS adaptive filter which we call the HOT block-LMS adaptive filter. This filter requires slightly less than half of the computations that are required for the FFT block-LMS adaptive filter. The simulations show that the convergence rates of both the HOT and FFT block-LMS adaptive filters are similar.

Keywords

adaptive filters; convolution; entropy; fast Fourier transforms; least mean squares methods; FFT; Hirschman optimal transform filter; block LMS adaptive filter; convolution theorem; entropy-based uncertainty; Adaptive filters; Computational efficiency; Convergence; Convolution; Discrete Fourier transforms; Discrete transforms; Frequency; Least squares approximation; Measurement uncertainty; Time measurement; adaptive filters; entropy; fast Fourier transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on

Conference_Location

Honolulu, HI

ISSN

1520-6149

Print_ISBN

1-4244-0727-3

Type

conf

DOI

10.1109/ICASSP.2007.367084

Filename

4217957