Fast system identification using affine projection and a critically sampled subband adaptive filter
Classical least-mean-square (LMS) adaptive filtering algorithms for system identification are popular and conceptually simple. In many applications subband adaptive filter structures have been shown to be superior computationally and performance-wise. This paper presents a novel subband affine projection algorithm (APA) suitable for use within a recently proposed adaptive filter structure employing critically sampled filter banks. The algorithm is described in the context of measuring a room impulse response for acoustic echo cancellation in hands-free telephony. Experimental results with speech input signals in a conference room show that a four-channel subband adaptive filter with subband APA can achieve an average 5 dB lower mean square error than a subband normalized LMS.
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|IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference|
|Organisation||Department of Systems and Computer Engineering|
Gordy, J.D., & Goubran, R. (2005). Fast system identification using affine projection and a critically sampled subband adaptive filter. Presented at the IMTC'05 - Proceedings of the IEEE Instrumentation and Measurement Technology Conference.