Perfect Sequence LMS For Rapid Acquisition Of Continuous-Azimuth Head Related Impulse Responses

Authors:

Antweiler, C. ,  Enzner, G.

Book Title:

Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)

Organization:

IEEE

Pages:

p.p. 281-284

Address:

New Paltz, NY, USA

Date:

Oct. 2009

ISBN:

978-1-42443-679-8

ISSN:

1931-1168

Language:

English

Abstract

In recent publications, continuous-azimuth inference of head related impulse responses (HRIRs) was treated as a time-varying system identification problem on the basis of dynamical measurements. The system identification thus can be handled by LMS-type adaptive filters for which we have the freedom to choose the excitation signal in this application. In order to provide the perspective of reducing the measurement time to a minimum, we now suggest the optimal excitation signal in terms of the rate of convergence. This excitation signal is given by perfect sequences (PSEQs) out of the larger family of periodic pseudo-noise signals. After the discussion of specific implications of perfect sequences, we compare the performances of our perfect-sequence LMS algorithm (PSEQLMS) to the results of white noise processing. We demonstrate a uniform improvement by PSEQ-LMS in terms of instrumental mean-square error analysis as well as subjective listening to dynamic HRIRs. Both measures turn out to be consistent.

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