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Volume 31 Issue 5
Dec.  2010
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Lin Chuan, Feng Quan-yuan. Combined Adaptive Filtering Algorithm Based on the Idea of Particle Swarm Optimization[J]. Journal of Electronics & Information Technology, 2009, 31(5): 1245-1248. doi: 10.3724/SP.J.1146.2008.00407
Citation: Lin Chuan, Feng Quan-yuan. Combined Adaptive Filtering Algorithm Based on the Idea of Particle Swarm Optimization[J]. Journal of Electronics & Information Technology, 2009, 31(5): 1245-1248. doi: 10.3724/SP.J.1146.2008.00407

Combined Adaptive Filtering Algorithm Based on the Idea of Particle Swarm Optimization

doi: 10.3724/SP.J.1146.2008.00407
  • Received Date: 2008-04-08
  • Rev Recd Date: 2008-09-05
  • Publish Date: 2009-05-19
  • Based on the social psychology idea behind the Particle Swarm Optimization (PSO) algorithm and the feature of adaptive FIR filter, the proper expressions for the inertial, cognitive and social parts are designed and applied to the optimization of the adaptive FIR filter in the combined adaptive filter. A combined adaptive filtering algorithm based on the idea of PSO is presented, and the complexity of the new algorithm is also analyzed. The theory analysis and the simulation results of the adaptive system identification under different conditions show that the new algorithm can balance the steady state misadjustment and tracking ability well, and its convergence performance is better than that of some other new LMS algorithms.
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  • 罗小东, 贾振红, 王强. 一种新的变步长LMS 自适应滤波算法[J]. 电子学报, 2006, 34(6): 1123-1126.Luo Xiao-dong, Jia Zhen-hong, and Wang Qiang. A newvariable step size LMS adaptive filtering algorithm[J]. ActaElectronica Sinica, 2006, 34(6): 1123-1126.[2]林川, 冯全源. 模糊步长LMS 算法及其性能分析[J]. 系统工程与电子技术, 2007, 29(6): 967-970.Lin Chuan and Feng Quan-yuan. Fuzzy step size LMSalgorithm and its performance analysis[J]. SystemsEngineering and Electronics, 2007, 29(6): 967-970.[3]Aboulnasr T and Mayyas K. A robust variable step-sizeLMS-type algorithm: analysis and simulations[J].IEEETrans. on Signal Processing.1997, 45(3):631-639[4]谷源涛, 唐昆, 崔慧娟等. 独立假设下的最优变步长LMS 模型和算法[J]. 中国科学(E 辑), 2003, 33(8): 760-768.Gu Yuan-tao, Tang Kun, and Cui Hui-juan, et al.. Optimalvariable step size LMS model and algorithm based on theindependence assumption[J]. Science in China (Series E),2003, 33(8): 760-768.[5]谷源涛, 唐昆, 崔慧娟. 步长选择定理及其应用[J]. 中国科学(E 辑), 2003, 33(10): 947-953.Gu Yuan-tao, Tang Kun, and Cui Hui-juan, et al.. Step sizeselection theorem and its applications[J]. Science in China(Series E), 2003, 33(10): 947-953.[6]Martinez-Ramon M, Arenas-Garcia J, and Navia-Vazquez A,et al.. An adaptive combination of adaptive filters for plantidentification[C]. 14th International Conference on DigitalSignal Processing, Piscataway: IEEE Press, 2002: 1195-1198.[7]Arenas-Garcia J, Gmez-Verdejo V, and Figueiras-Vidal A R.New algorithms for improved adaptive convex combination ofLMS transversal filters[J].IEEE Trans. on Instrumentationand Measurement.2005, 54(6):2239-2249[8]Arenas-Garcia J, Figueiras-Vidal A R, and Sayed A H. Meansquareperformance of a convex combination of two adaptivefilters[J].IEEE Trans. on Signal Processing.2006, 54(3):1078-1090[9]Shi Y and Eberhart R C. A modified particle swarmoptimizer[C]. Proceedings of the IEEE InternationalConference on Evolutionary Computation. IEEE Press,Piscataway, NJ, 1998: 69-73.[10]林川, 冯全源. 基于微粒群本质特征的混沌微粒群优化算法[J]. 西南交通大学学报, 2007, 42(6): 665-669.Lin Chuan, Feng Quan-yuan. Chaotic particle swarmoptimization algorithm based on the essence of particleswarm[J]. Journal of Southwest Jiaotong University, 2007,42(6): 665-669.[11]Krusienski D J and Jenkins W K. Design and performance ofadaptive systems based on structured stochastic optimizationstrategies[J].IEEE Circuits and Systems Magazine.2005,5(1):8-20
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