.png){kind=icon}
Return
An Improved Multiband-Structured Subband Adaptive Filter Algorithm
.png){kind=icon}
PRE
AI
DOI：10.1109/LSP.2012.2210213.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Recently, a multiband-structured subband adaptive filter (MSAF) algorithm was proposed to speed up the convergence of the normalized least-mean-square (NLMS) algorithm. In this letter, we extend this work and propose an improved multiband-structured subband adaptive filter (IMSAF) algorithm to increase the convergence speed of the MSAF, which can also be regarded as a unifying framework for the NLMS, MSAF, and affine projection (AP) algorithms. The proposed optimization criterion is based on the principle of minimal disturbance, canceling the most recent P a posteriori errors in each of the N subbands. The stability condition and the computational complexity are also analyzed. Computer simulations in the context of system identification demonstrate the effectiveness of the new algorithm.
Keywords:
Acoustic echo cancellation
convergence rate
subband adaptive filter
subband update
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
9.6
Papers:
1.1W
Citations:
1.7W
Organization
Cited Papers
.png){kind=icon}
ShareSave
ShareSaveShareSave
View more