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

@article{Yang2003MultiuniversePQ,
  title={Multi-universe parallel quantum genetic algorithm its application to blind-source separation},
  author={Jun-an Yang and Bin Li and Zhenquan Zhuang},
  journal={International Conference on Neural Networks and Signal Processing, 2003. Proceedings of the 2003},
  year={2003},
  volume={1},
  pages={393-398 Vol.1}
}
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). 
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