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Multi-universe parallel quantum genetic algorithm its application to blind-source separation

机译:多宇宙并行量子遗传算法在盲源分离中的应用

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This paper first proposes a novel multi-universe parallel quantum genetic algorithm (MPQGA). Then it puts forward a new blind source separation (BSS) method based on the combination of MPQGA and independent component analysis (ICA). The simulation result shows that the efficiency of the new BSS method is obviously higher than that of the conventional genetic algorithm (CGA) and the quantum genetic algorithm (QGA).
机译:本文首先提出了一种新颖的多宇宙并行量子遗传算法(MPQGA)。然后提出了一种基于MPQGA和独立分量分析(ICA)相结合的盲源分离(BSS)方法。仿真结果表明,新的BSS方法的效率明显高于常规遗传算法(CGA)和量子遗传算法(QGA)。

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