Fast System Identification Using Direct Matrix Inversion and a Critically Sampled Subband Adaptive Filter

Bao Cheng-hao; Shui Peng-lang

doi:10.3724/SP.J.1146.2006.00831

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Bao Cheng-hao, Shui Peng-lang . Fast System Identification Using Direct Matrix Inversion and a Critically Sampled Subband Adaptive Filter[J]. Journal of Electronics & Information Technology, 2008, 30(1): 139-143. doi: 10.3724/SP.J.1146.2006.00831

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Bao Cheng-hao, Shui Peng-lang . Fast System Identification Using Direct Matrix Inversion and a Critically Sampled Subband Adaptive Filter[J]. Journal of Electronics & Information Technology, 2008, 30(1): 139-143. doi: 10.3724/SP.J.1146.2006.00831

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Fast System Identification Using Direct Matrix Inversion and a Critically Sampled Subband Adaptive Filter

doi: 10.3724/SP.J.1146.2006.00831

Received Date: 2006-06-13
Rev Recd Date: 2006-12-20
Publish Date: 2008-01-19

Abstract

Abstract

In many applications subband adaptive filter structures have been shown to be superior computationally and performancewise. This paper presents a subband Direct Matrix Inversion (DMI) algorithm suitable for use within a recently proposed adaptive filter structure employing critically sampled filter banks. This new method reduces the computational complexity by using the block tridiagonal structure of the input sample correlation matrix, and at the same time keeps the advantage of fast convergence. Experimental results show that the output residue power of the subband DMI algorithm is around 3dB upon the optimum value after only 2K updating of the adaptive subfilters, where K is the dimension of the adaptive subfilters.

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References(1)

References

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