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《电子科学学刊(英文版)》 2003-01
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RESEARCH OF QUANTUM GENETIC ALGORITH AND ITS APPLICATION IN BLIND SOURCE SEPARATION

Yang Junan Li Bin Zhuang Zhenquan (Department of Electronic Science & Technology, USTC, Hefei 230026)  
This letter proposes two algorithms: a novel Quantum Genetic Algorithm (QGA) based on the improvement of Han's Genetic Quantum Algorithm (GQA) and a new Blind Source Separation (BSS) method based on QGA 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).
【Fund】: Supported by the National Natural Science Foundation of China (No.60171029)
【CateGory Index】: TP18
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