Blind Source Separation in Underdetermined Model based on Local Mean Decomposition and AMUSE Algorithm

摘要：

　　An objective of blind source separation(BSS)is to recover potential source signals from their mixtures without a prior knowledge of the mixing process.In this paper,a new underdetermined blind source separation(UDBSS)approach,based on the local mean decomposition(LMD)method and the AMUSE algorithm,is proposed.To make the UDBSS problem simpler,some extra observation signals are first constructed using the LMD method.Thus the underdetermined blind source separation problem is transformed into an(over-)determined one.Subsequently,the well known AMUSE algorithm is applied to these new observations to estimate the source signals.The proposed method does not resort to the sparsity constraint which is included in most of the former researches.The theoretical analysis and simulation results illustrate the effectiveness of the proposed UDBSS method.

关键词： Blind source separation Local mean decomposition Underdetermined mixture AMUSE algorithm

作者: LI Wei YANG Huizhong

作者单位: Key Laboratory of Advanced Process Control for Light Industry of Jiangnan University,Wuxi 214122,Jiangsu,P.R.China

会议类型: 国际会议

会议名称: The 33th Chinese Control Conference第33届中国控制会议

会议地点: 南京

会议语种:英文

页码: 7206-7211

在线出版日期: 2014-07-28（万方平台首次上网日期，不代表论文的发表时间）