Work

Selective-tap blind signal processing for speech separation

Year: 2009

Type: conference-paper

Abstract: In this paper, we propose a new blind multichannel adaptive filtering scheme, which incorporates a partial-updating mechanism in the error gradient of the update equation. The proposed blind processing algorithm operates in the time-domain by updating only a selected portion of the adaptive filters. The algorithm steers all computational resources to filter taps having the largest magnitude gradient components on the error surface. Therefore, it requires only a small number of updates at each iteration and can substantially minimize overall computational complexity. Numerical experiments carried out in realistic blind identification scenarios indicate that the performance of the proposed algorithm is comparable to the performance of its full-update counterpart, but with the added benefit of a highly reduced computational complexity.

Source: Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

DOI: 10.1109/iembs.2009.5334033

Authors: K. Kokkinakis, P.C. Loizou

Institution: The University of Texas at Dallas

Language: English

Topic: Advanced Adaptive Filtering Techniques

Subfield: Computational Mechanics

Field: Engineering

Domain: Physical Sciences

Open Access status: green

Funder: National Institute on Deafness and Other Communication Disorders

Awards: Optimizing speech coding strategies for noise and music, Blind Processing for Better Speech Recognition with Cochlear Implant Devices