Title :
Research of nonlinear blind source separation algorithm based on quantum evolutionary neural network
Author :
Yang, Jun-an ; Peng, Hui ; Zhuang, Zhenquan
Author_Institution :
Dept. of Electron. Sci. & Technol., Univ. of Sci. & Technol. of China, Hefei, China
Abstract :
This paper analyzes the neural network model and algorithm of nonlinear blind source separation (NBSS) systematically, discusses the existence and uniqueness of solution of NBSS, puts forward a novel NBSS algorithm based on mutual cumulates, and uses multi-universe parallel quantum genetic algorithm (MPQGA) to acquire its optimum solution. The simulation result demonstrates the effectiveness of the algorithm.
Keywords :
blind source separation; evolutionary computation; genetic algorithms; neural nets; parallel algorithms; quantum computing; quantum theory; multiuniverse parallel quantum genetic algorithm; mutual cumulates; neural network model; nonlinear blind source separation; quantum evolutionary neural network; Adaptive signal processing; Algorithm design and analysis; Biomedical signal processing; Blind source separation; Electronic mail; Genetic algorithms; Neural networks; Signal processing algorithms; Source separation; Statistics;
Conference_Titel :
Machine Learning and Cybernetics, 2003 International Conference on
Print_ISBN :
0-7803-8131-9
DOI :
10.1109/ICMLC.2003.1259594
