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基于多宇宙并行量子遗传算法的非线性盲源分离算法研究 被引量:10

Nonlinear Blind Source Separation Algorithm Using Multi-universe Parallel Quantum Genetic Algorithm
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摘要 在系统分析非线性盲源分离模型和算法的基础上,提出了基于输出信号联合累积量的非线性盲 源分离算法,并提出采用多宇宙并行量子遗传算法的优化求解方法,仿真结果表明了算法的有效性. This paper analyzes the model and algorithm of Nonlinear Blind Source Sepa-ration(NBSS) systematically, proposes a novel NBSS algorithm based on mutual cumulates, and puts forward a new optimum method using Multi-universe Parallel Quantum Genetic Algorithm(MPQGA). The simulation result demonstrates the effectiveness of the algorithm.
出处 《电子与信息学报》 EI CSCD 北大核心 2004年第8期1210-1217,共8页 Journal of Electronics & Information Technology
基金 973国家重点基础研究发展规划项目(G1998030413) 国家自然科学基金项目(No.60171029)资助课题
关键词 非线性盲源分离 联合累积量 量子计算 量子遗传算法 多宇宙并行量子遗传算法 Nonlinear Blind Source Separation(NBSS), Mutual cumulates, Quantum computation, Quantum genetic algorithm, Multi-universe Parallel Quantum Genetic Al-gorithm(MPQGA)
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