Title :
Multi-universe parallel quantum genetic algorithm its application to blind-source separation
Author :
Yang, Jun-an ; Li, Bin ; Zhenquan Zhuang
Author_Institution :
Hefei Electron. Eng. Inst., China
Abstract :
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).
Keywords :
blind source separation; genetic algorithms; independent component analysis; parallel algorithms; quantum computing; blind-source separation; conventional genetic algorithm; independent component analysis; multiuniverse parallel quantum genetic algorithm; Biological cells; Blind source separation; Concrete; Databases; Genetic algorithms; Independent component analysis; Q measurement; Quantum computing; Rotation measurement; Source separation;
Conference_Titel :
Neural Networks and Signal Processing, 2003. Proceedings of the 2003 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
0-7803-7702-8
DOI :
10.1109/ICNNSP.2003.1279292
