Improved FastICA Algorithm Based on Symmetic Orthogonalization

摘要：

　　The convergence of fast independent component analysis (FastICA) algorithm based on the Newton iterative method was depended on initial value.So the different initial values could result in the different convergence speeds.To deal with this problem,this paper is proposed an improved FastICA algorithm based on symmetric orthogonalization.The algorithm selected initial value randomly,and used serial orthogonalization to get the suitable initial separating matrix firstly.Then it used symmetric orthogonalization to get the separating matrix.Finally,it could get the separated signals.Simulation results show that the proposed algorithm has faster convergence speed than the original and another improved FastICA algorithm with the same signal separation accuracy.

关键词： blind signal separation FastICA serial orthogonalization symmetric orthonormalization convergence speed

作者: Dabao Zhang Hong Shao

作者单位: Peoples Broadcast Station of Henan, Zhengzhou, China Quality and Technical Supervision and Inspection Testing Center, Anyang, China

会议类型: 国际会议

会议名称: 2012 IEEE 11th International Conference on Signal Processing (第11届IEEE信号处理国际会议)

会议地点: 北京

会议语种:英文

页码: 75-78

在线出版日期: 2012-10-21（万方平台首次上网日期，不代表论文的发表时间）