Accounting for measurement noise color in frequency domain adaptive algorithms

Author

Trump, Tõnu

Author_Institution

Ericsson Radio Syst. AB, Stockholm, Sweden

Volume

1

fYear

1998

fDate

1-4 Nov. 1998

Firstpage

508

Abstract

A method of using a partial knowledge of measurement noise in frequency domain adaptive algorithms is considered. Overlap-save and overlap-add type adaptive schemes are both investigated. The algorithms are derived by minimizing a best linear unbiased estimators (BLUE) criterion function using the stochastic gradient method and then switching over to the frequency domain to reduce the computational complexity. The performance of the algorithms is investigated via simulations using stationary as well as speech signals.

Keywords

adaptive signal processing; computational complexity; frequency-domain analysis; gradient methods; measurement; noise; parameter estimation; speech processing; stochastic processes; BLUE criterion function minimisation; best linear unbiased estimators; computational complexity reduction; frequency domain adaptive algorithms; measurement noise color; overlap-add adaptive scheme; overlap-save adaptive scheme; partial knowledge; signal processing; simulations; speech signals; stationary signals; stochastic gradient method; Adaptive algorithm; Colored noise; Computational complexity; Computational modeling; Frequency domain analysis; Frequency estimation; Frequency measurement; Gradient methods; Noise measurement; Stochastic resonance;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems & Computers, 1998. Conference Record of the Thirty-Second Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-7803-5148-7

Type

conf

DOI

10.1109/ACSSC.1998.750915

Filename

750915