FIR Frequency Sampling Filters Design Based on Adaptive Particle Swarm Optimization Algorithm

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• 作者：Wanping Huang ; Lifang Zhou ; Jixin Qian ; Longhua Ma
• 关键词：particle swarm optimization ; adaptive capacity ; FIR filter ; frequency sampling filter ; evolutionary computation
• 刊名：Lecture Notes in Computer Science
• 出版年：2005
• 出版时间：2005
• 年：2005
• 卷：3612
• 期：1
• 页码：p.289
• 全文大小：220 KB

文摘

Based on the study of Particle Swarm Optimization (PSO) on the mechanism of information communion, a new adaptive method of PSO is presented in this paper. This new adaptive method is to avoid the particles getting into local best solution during the optimization. By applying Adaptive Particle Swarm Optimization (APSO) to optimize transition sample values in FIR filter, the maximum stop band attenuation is obtained. The simulations of designing low-pass FIR have been done and the simulation results show that APSO is better than PSO not only in the optimum ability but also in the convergence speed.