| 基于PSO算法的测试信号模型参数提取 |
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| 引用本文： | 朱赛,蔡金燕,杜敏杰. 基于PSO算法的测试信号模型参数提取[J]. 计算机工程与设计, 2012, 33(6): 2432-2436 |
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| 作者姓名： | 朱赛 蔡金燕 杜敏杰 |
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| 作者单位： | 军械工程学院 光学与电子工程系,河北石家庄,050003 |
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| 基金项目： | 河北省重点基础研究基金项目 |
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| 摘 要： | 为了提高自动测试系统的自动化水平,提出了基于粒子群算法的测试信号模型参数提取方法.阐述了采用PSO算法提取测试信号模型参数的原理,针对参数提取过程中的早熟收敛问题,提出了一种改进算法.该算法监控粒子群多样性,采用局部初始化的方法,克服了早熟收敛的缺点,提高了参数提取的稳定性.仿真实验验证了基于PSO算法的测试信号模型参数提取方法具有较高的稳定性和精度.
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| 关 键 词： | 测试信号模型 参数提取 PSO算法 早熟收敛 熵 |
Test signal model parameter extraction based on PSO algorithm |
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| ZHU Sai , CAI Jin-yan , DU Min-jie. Test signal model parameter extraction based on PSO algorithm[J]. Computer Engineering and Design, 2012, 33(6): 2432-2436 |
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| Authors: | ZHU Sai CAI Jin-yan DU Min-jie |
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| Affiliation: | (Ordnance Engineering College,Department of Electronic and Optical Engineering,Shijiazhuang 050003) |
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| Abstract: | To raise the automation level of ATS,the test signal model parameter extraction based on particle swarm optimization(PSO) algorithm is presented.The theory of PSO based parameter extraction method is illustrated.To prevent the problem of premature convergence frequently appeared in the parameter extraction,an improved method is proposed,which initialize part particles through tracking the diversity of particle swarm.The problem of premature convergence is prevented and the stability of parameter extraction is increased.Simulation results show that PSO algorithm based on test signal model parameter extraction method has good performance. |
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| Keywords: | test signal model parameter extraction particle swarm optimization premature convergence entropy |
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