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论文:2013,Vol:31,Issue(2):183-188 |
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引用本文: |
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智永锋, 郑曦, 李茹, 邓正宏, 张骏. 一种变步长AP-REE算法的研究[J]. 西北工业大学 |
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Zhi Yongfeng, Zheng Xi, Li Ru, Deng Zhenghong, Zhang Jun. A Better Variable Step-Size (VSS) Affine Projection (AP) Algorithm Using Regressive Estimated Error (REE)[J]. Northwestern polytechnical university |
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一种变步长AP-REE算法的研究 |
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智永锋, 郑曦, 李茹, 邓正宏, 张骏 |
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西北工业大学 自动化学院, 陕西 西安 710072 |
摘要: |
为了提高自适应滤波器的滤波性能,提出了一种变步长的AP-REE算法。通过分析AP-REE算法权值误差和权值均方误差的二阶统计量,获得了参数迭代步长的一个优化解,促进了AP-REE算法在迭代方向上均方误差的收敛速度。仿真结果表明,相比较于定步长的AP-REE算法,变步长的AP-REE算法获得了更快的收敛速度。 |
关键词:
自适应滤波
算法
计算机仿真
数值法的收敛性
优化估计
变步长AP-REE算法
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A Better Variable Step-Size (VSS) Affine Projection (AP) Algorithm Using Regressive Estimated Error (REE) |
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Zhi Yongfeng, Zheng Xi, Li Ru, Deng Zhenghong, Zhang Jun |
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Department of Automatic Control,Northwestern Polytechnical University,Xi'an 710072,China |
Abstract: |
Aim. To improve the convergence rate performance of an adaptive filter, especially for the highly coloredinput signals,Refs. 2 and 3 adopt the AP algorithm. Ref. 11 adopts AP-REE algorithm by redefining the iteratederror for the AP algorithm. However,its gain does not change,and thus its convergence is not as rapid as is possi-ble,in our opinion,with adaptive gain. We explain mathematically in sections 1,2 and 3 of the full paper ourVSS-AP-REE algorithm and explain how it achieves optimization. The simulation results,shown in Figs. 1 and 2,and their analysis indicate preliminarily that our VSS-AP-REE algorithm has faster convergence performance ascompared with the conventional AP-REE algorithm. |
Key words:
adaptive filtering
algorithms
computer simulation
convergence of numerical methods
estimation
optimization;VSS-AP-REE (variable step-size affine projection using regressive estimated error) al-gorithm
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收稿日期: 2012-05-12
修回日期:
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DOI: |
基金项目: 国家自然科学基金(61201321);西北工业大学基础研究基金(JC20100217)资助 |
通讯作者:
Email: |
作者简介: 智永锋(1979-),西北工业大学讲师,主要从事自适应滤波算法的研究。
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相关功能 |
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作者相关文章 |
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智永锋 在本刊中的所有文章 |
郑曦 在本刊中的所有文章 |
李茹 在本刊中的所有文章 |
邓正宏 在本刊中的所有文章 |
张骏 在本刊中的所有文章 |
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参考文献: |
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[1] Haykin Simon. Adaptive Filter Theory, 4th ed. New Jersey: Prentice-Hall, 2002 [2] Ozeki K,Umeda T. An Adaptive Filtering Algorithm Using an Orthogonal Projection to an Affine Subspace and Its Properties.Electronics and Communications in Japan, 1984, 67-A (5): 19-27 [3] Rupp M. A Family of Adaptive Filter Algorithms with Decorrelating Properties. IEEE Trans On Signal Processing,1998,46(3): 771-775 [4] Sankaran S G,Beex A A. Fast Generalized Affine Projection Algorithm. International Journal of Adaptive Control and SignalProcessing, 2000, 14(6): 623-641 [5] Sankaran S G,Beex A A. Convergence Behavior of Affine Projection Algorithms. IEEE Trans on Signal Processing,2000,48(4): 1086-1096 [6] Paul T K,Ogunfunmi T. On the Convergence Behavior of the Affine Projection Algorithm for Adaptive Filters. IEEE Trans onCircuits and Systems, 2011, 58(8): 1813-1826 [7] Almeida S J M D, Bermudez J C M, Bershad N J, Costa M H. A Statistical Analysis of the Affine Projection Algorithm for UnityStep Size and Autoregressive Inputs. IEEE Trans on Circuits and Systems, 2005, 52(7): 1394-1405 [8] Almeida S J M D,Bermudez J C M,Bershad N J. A Stochastic Model for a Pseudo Affine Projection Algorithm. IEEE Trans onSignal Processing, 2009, 57(1): 107-118 [9] Kim S E,Lee J W,Song W J. A Theory on the Convergence Behavior of the Affine Projection Algorithm. IEEE Trans on SignalProcessing, 2011, 59(12): 6233-6239 [10] Zhi Y F,Zhang J, Li Y X. Steady-State Weights Solution of Affine Projection Algorithm. Journal of Control Theory and Applica-tions, 2012, 10(2): 259-263 [11] Zhang S,Zhi Y F. Affine Projection Algorithm with Regressive Estimated Error. ISRN Signal Processing,2011,∥http:www.hindawi. com/sirn/sp/2011/180624/ [12] Papoulis A. Probability,Random Variables,and Stochastic Processes. Ist ed. NY: McGraw-Hill, 1965 |
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