基于反向学习的粒子群算法对线性相位低通FIR滤波器的优化

doi:10.13229/j.cnki.jdxbgxb201503032

吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (3): 907-912.doi: 10.13229/j.cnki.jdxbgxb201503032

基于反向学习的粒子群算法对线性相位低通FIR滤波器的优化

邵鹏^{1, 2}, 吴志健^{1, 2}, 周炫余²

1.武汉大学软件工程国家重点实验室,武汉 430072;
2.武汉大学计算机学院,武汉 430072

收稿日期:2013-09-23 出版日期:2015-05-01 发布日期:2015-05-01
通讯作者: 吴志健(1963-),男,教授,博士生导师.研究方向:智能计算,反问题,并行计算. E-mail:sp198310@163.com
作者简介:邵鹏(1983-),男,博士研究生.研究方向:智能计算,智能信息处理.
基金资助:
国家自然科学基金项目(61070008,70971043); 武汉大学软件工程国家重点实验室开放基金项目(SKLSE2012-09-19); 中央高校基本科研业务费专项项目(2012211020205); 江西省教育厅科学技术项目(GJJ13729)

Particle swarm optimization algorithm based on opposite learning for linear phase low-pass FIR filter optimization

SHAO Peng^{1, 2}, WU Zhi-jian^{1, 2}, ZHOU Xuan-yu²

1.State Key Lab of Software Engineering, Wuhan University, Wuhan 430072, China;
2.Computer School, Wuhan University, Wuhan 430072, China

Received:2013-09-23 Online:2015-05-01 Published:2015-05-01

摘要/Abstract

摘要： 将一种基于反向学习的改进粒子群优化算法(OPPSO)应用于设计具有线性相位的低通FIR数字滤波器。该算法通过求解粒子位置的反向解来增加找到最优解的概率,从而求得一组使所述滤波器最优的参数组合。同时,在试验中引入一种更具有现实意义的接近于理想滤波器的零相位滤波器作为对比。试验结果表明,该算法在设计线性相位低通FIR数字滤波器上具有良好的优化效果。

关键词: 人工智能, 粒子群优化算法, 有限脉冲响应, 数字滤波器, 反向学习

Abstract: Finite Impulse Response (FIR) digital filter design is actually the design of unit impulse response coefficients combination, which is essentially a combination of multi-parameter optimization problem. On this basis, an improved particle swarm optimization algorithm based on opposite learning strategy (OPPSO) is applied to design linear phase low-pass FIR digital filter. OPPSO increases the probability to find the optimal solution by solving the inverse solution of the particle position, thus, to find a set of optimal combination of parameters of the filter. Meanwhile, a more realistic sense of zero phase filters close to the ideal filter is introduced into the experiment for comparison. Experimental results show that the proposed algorithm has good optimal results for linear phase low-pass FIR digital filter design.

Key words: artificial intelligence, particle swarm optimization, finite impulse response, digital filter, opposite learning

中图分类号:

TP18

邵鹏, 吴志健, 周炫余. 基于反向学习的粒子群算法对线性相位低通FIR滤波器的优化[J]. 吉林大学学报(工学版), 2015, 45(3): 907-912.

SHAO Peng, WU Zhi-jian, ZHOU Xuan-yu. Particle swarm optimization algorithm based on opposite learning for linear phase low-pass FIR filter optimization[J]. 吉林大学学报(工学版), 2015, 45(3): 907-912.

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基于反向学习的粒子群算法对线性相位低通FIR滤波器的优化

Particle swarm optimization algorithm based on opposite learning for linear phase low-pass FIR filter optimization

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