A Blind Source Separation Method Based on Kalman Filtering
According to Nonlinear Principal Component Analysis (NPCA) criterion, a blind source separation algorithm based on Kalman filtering is proposed in this paper. The convergence property of the algorithm is analyzed. The performance of the algorithm is evaluated by using several different kinds of sources. The effect of the number of iteration steps and the observation noise for the performance are investigated. The results show that this algorithm can separate chaotic as well as other sources from linear instantaneous mixtures effectively.
Zhihui Hu Jiuchao Feng
School of Electronic & Information Engineering, South China University of Technology, Guangzhou 510641, China
国际会议
2009国际通信电路与系统学术会议(ICCCAS 2009)(2009 International Conference on Communications，Circuits and Systems)
成都
英文
473-476
2009-07-23（万方平台首次上网日期，不代表论文的发表时间）