An ICA-based Adaptive Filter Algorithm for System Identification Using A State Space Approach

摘要：

This paper proposes a new ICA-based adaptive filter algorithm for system identification using a state space approach.An additive noise model is considered and the signal is separated from the noisy observation.First,we introduce an augmented state-space expression of the observed signal representing the problem in terms of ICA,and then using the natural gradient,we derive a new algorithm.The local convergence conditions of the proposed algorithm is derived.Some simulations are carried out to illustrate its effectiveness.

作者: Jun-Mei Yang Hideaki Sakai

作者单位: Graduate School of Informatics,Kyoto University,Kyoto,606-8501,Japan;School of Electronic & Informat Graduate School of Informatics,Kyoto University,Kyoto,606-8501,Japan

会议类型: 国际会议

会议名称: 9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-26（万方平台首次上网日期，不代表论文的发表时间）