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基于PPSO-GRADS算法的盲信号分离
引用本文:陈永强, 田亚菲. 基于PPSO-GRADS算法的盲信号分离[J]. 电子与信息学报, 2007, 29(8): 1817-1820. doi: 10.3724/SP.J.1146.2005.01459
作者姓名:陈永强  田亚菲
作者单位:成都信息工程学院,成都,610225;成都信息工程学院,成都,610225;成都信息工程学院,成都,610225
摘    要:该文将联姻策略应用在粒子群算法中,提出一种并行分阶段的基于粒子群优化算法的盲信号分离方法(PPSO-GRADS)。该算法具有收敛速度快,分离精度高的特点。通过仿真证明该算法比未使用联姻策略的粒子群算法有更好的性能,在收敛速度和分离效果上比传统的梯度算法,遗传算法都有较明显的改善。

关 键 词:盲信号分离  粒子群算法  独立分量分析  联姻策略
文章编号:1009-5896(2007)08-1817-04
收稿时间:2005-11-15
修稿时间:2005-11-15

Blind Signal Separation Based on PPSO-GRADS Algorithm
Chen Yong-qiang, Tian Ya-fei. Blind Signal Separation Based on PPSO-GRADS Algorithm[J]. Journal of Electronics & Information Technology, 2007, 29(8): 1817-1820. doi: 10.3724/SP.J.1146.2005.01459
Authors:Chen Yong-qiang  Tian Ya-fei
Affiliation:School of Information Science & Engineering, Lanzhou University, Lanzhou 730000, China; Chengdu University of Information Technology, Chengdu 610225, China
Abstract:In this paper, allied strategy is introduced into PSO and a parallel and two-stage blind signal separation based on particle swarm optimization (parallel particle swarm optimization—gradient algorithm) is proposed. This algorithm is characteristic of rapid convergent speed and high separation precision. The simulation results show that this algorithm proposed is superior to particle swarm optimization in which allied strategy is not applied, and this algorithm is superior to traditional gradient algorithm and genetic algorithm in convergent speed and separation effect.
Keywords:Blind signal separation  Particle swarm optimization  Independent component analysis  Allied strategy
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