과거계수 벡터를 이용한멀티밴드 구조 부밴드 적응 필터링 알고리즘

초록

In this paper, an improved multiband-structured subband adaptive filter using past weight vectors is proposed. In case of high background noise, heavy fluctuation can occur in the estimated weight vector since the conventional subband adaptive filtering algorithm updates the next weight vector by using the present weight vector. To solve the problem, we propose a new method of updating the present weight vector in the multiband- structured subband adaptive filter by averaging present and past weight vectors. Through the proposed method, we use past weight vectors for subband adaptive filtering algorithm using an affine projection method at first, whereby the number of past weight vectors is adaptively determined. Computer simulation results demonstrate the robust performance of the proposed algorithm even in case of high background noise. Also, it is shown that the convergence speed can be improved by adaptively controlling the number of past weight vectors depending on the output error information.

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