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Combined Adaptive Filtering Algorithm Based on the Idea of Particle Swarm Optimization |
Lin Chuan; Feng Quan-yuan |
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 610031, China |
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Abstract 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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Received: 08 April 2008
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