归一化子带自适应滤波器步长控制

倪锦根; 商慧亮; 李锋

doi:10.3724/SP.J.1146.2008.01708

归一化子带自适应滤波器步长控制

doi: 10.3724/SP.J.1146.2008.01708

计量
- 文章访问数: 3742
- HTML全文浏览量: 137
- PDF下载量: 792
- 被引次数: 0
出版历程
- 收稿日期: 2008-12-15
- 修回日期: 2009-05-18
- 刊出日期: 2009-11-19

Step-Size Control for the Normalized Subband Adaptive Filter

摘要

摘要: 定步长子带自适应滤波器必须在快的收敛速度和低的稳态失调之间进行折中。根据自适应滤波器系数向量均方偏差与步长之间的函数关系，该文采用使自适应滤波器系数向量均方偏差在每次迭代更新时最速下降的方法，提出一种步长控制算法来解决上述问题。该算法可以兼得快的收敛速度和低的稳态失调。实验结果验证了该方法的有效性。
- 子带自适应滤波器; 步长控制; 均方偏差
Abstract: Fixed step-size Subband Adaptive Filters (SAFs) must carry out a trade-off between fast convergence rate and low steady-state misadjustment. According to the functional relationship between the Mean-Square Deviation (MSD) of the coefficient vector of the adaptive filter and step-size, this paper proposes a step-size control algorithm to address the problem above, which is derived by the largest decrease method of the MSD of the coefficient vector of the adaptive filter for each iterative update. This algorithm can obtain both fast convergence rate and low steady-state misadjustment. Experimental results verify the validity of the proposed method.

HTML全文

参考文献(1)

Haykin S. Adaptive Filter Theory [M]. Fourth edition, UpperSaddle River, NJ: Prentice-Hall, 2002, 22-34: 331-340.[2]Diniz P S R. Adaptive Filtering: Algorithms and PracticalImplementation [M]. Second edition, Boston: KluwerAcademic Publishers, 2002: 467-499.[3]Courville M D and Duhamel P. Adaptive filtering insubbands using a weighted criterion [J].IEEE Transactionson Signal Processing.1998, 46(9):2359-2371[4]Pradhan S S and Reddy V U. A new approach to subbandadaptive filtering [J].IEEE Transactions on SignalProcessing.1999, 47(3):655-664[5]Lee K A and Gan W S. Improving convergence of the NLMSalgorithm using constrained subband updates [J].IEEESignal Processing Letters.2004, 11(9):736-739[6]Miyagi S and Sakai H. Convergence analysis of alias-freesubband adaptive filters based on a frequency domaintechnique [J].IEEE Transactions on Signal Processing.2004,52(1):79-89[7]Lee K A and Gan W S. Inherent decorrelating and leastperturbation properties of the normalized subband adaptivefilter [J].IEEE Transactions on Signal Processing.2006,54(11):4475-4480[8]Lee K A and Gan W S. On the subband orthogonality ofcosine-modulated filter banks [J].IEEE Transactions onCircuits and Systems II: Express Briefs.2006, 53(8):677-681[9]Lee K A.[J].Gan W S, and Kuo S M. Mean-square performanceanalysis of the normalized subband adaptive filter [C]. TheFortieth Asilomar Conference on Signals, Systems Computers, Pacific Grove, California, October 29-November.2006,:-[10]Bershad N J, Bermudez J C M, and Tourneret J Y. An affinecombination of two LMS adaptive filtersTransientmean-square analysis [J].IEEE Transactions on SignalProcessing.2008, 56(5):1853-1864[11]Benesty J, Rey H, and Vega L R, et al.. A nonparametric VSSNLMS algorithm [J].IEEE Signal Processing Letters.2006,13(10):581-584[12]Shin H C, Sayed A H, and Song W J. Variable step-sizeNLMS and affine projection Algorithms[J].IEEE SignalProcessing Letters.2004, 11(2):132-135[13]Petraglia M R and Batalheiro P. Nonuniform subbandadaptive filtering with critical sampling[J].IEEE Transactionson Signal Processing.2008, 56(2):565-575[14]Kong S J, Hwang K Y, and Song W J. An affine projectionalgorithm with dynamic selection of input vectors [J].IEEESignal Processing Letters.2007, 14(8):529-532[15]Rey H, Vega L R, and Tressens S, et al.. Variable explicitregularization in affine projection algorithm: robustness andoptimal choice [J].IEEE Transactions on Signal Processing.2007, 55(5):2096-2109

施引文献

资源附件(0)

访问统计