| 求解多输入多输出检测新算法——遗传粒子群优化 |
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| 引用本文： | 黑永强,李晓辉,易克初,郁光辉.求解多输入多输出检测新算法——遗传粒子群优化[J].电波科学学报,2011(1):42-49. |
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| 作者姓名： | 黑永强 李晓辉 易克初 郁光辉 |
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| 作者单位： | 西安电子科技大学ISN国家重点实验室;深圳市中兴通讯技术有限公司; |
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| 基金项目： | 国家自然科学基金(60702060); 高等学校学科创新引智计划(B08038); 国家重点实验室专项基金(ISN03080005); 国家重大专项:IMT-A中的增强MIMO技术研发(2009ZX03003-005) |
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| 摘 要： | 设计两种基于粒子群优化算法(PSO)和基于遗传算法(GA)的多输入多输出(MIMO)系统检测算法.提出一种新的融合GA和PSO进化机制的遗传粒子群进化(GPSO)算法,并将其应用于MIMO系统检测问题求解.新算法改善了初始化种群,并将每一代粒子划为精英粒子、次优粒子和糟糕粒子三部分,对这三种粒子分别采用极值扰动、PSO...
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| 关 键 词： | 粒子群优化 遗传算法 检测 复杂度 |
New genetic particle swarm optimization evolutionary algorithm for MIMO detecting system |
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| HEI Yong-qiang LI Xiao-hui YI Ke-chu YU Guang-hui.New genetic particle swarm optimization evolutionary algorithm for MIMO detecting system[J].Chinese Journal of Radio Science,2011(1):42-49. |
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| Authors: | HEI Yong-qiang LI Xiao-hui YI Ke-chu YU Guang-hui |
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| Affiliation: | HEI Yong-qiang1 LI Xiao-hui1 YI Ke-chu1 YU Guang-hui2 (1.State Key Lab.of Integrated Services Networks,Xidian University,Xi'an Shaanxi 710071,China,2.ZTE Corporation in Shenzhen City,Shenzhen Guangdong 518057,China) |
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| Abstract: | Two MIMO detecting algorithms corresponding to particle swarm optimization(PSO)based and genetic algorithm(GA)based detecting algorithms are designed.A novel genetic particle swarm optimization(GPSO) evolutionary method is proposed and applied to address the MIMO detecting problem.The proposed algorithm starts from improving the initial population,and divide the entire population into three types: elite particles,better particles and worst particles.Three different strategies of optimum value permutation,PS... |
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| Keywords: | particle swarm optimization genetic algorithm detecting complexity |
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