Robust Huber M-estimator based proportionate affine projection algorithm with variable cutoff updating

作     者：Wu, Chao Wang, Xiaofei Guo, Yanmeng Fu, Qiang Yan, Yonghong 

作者机构：Chinese Acad Sci Beijing Peoples R China 

出 版 物：《ELECTRONICS LETTERS》 (电子学快报)

年 卷 期：2015年第51卷第25期

页      面：2113-2114页

核心收录：

学科分类：0808[工学-电气工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：National Natural Science Foundation of China [11161140319, 91120001, 61271426] Strategic Priority Research Program of the Chinese Academy of Sciences [XDA06030100, XDA06030500] National 863 Program [2012AA012503] CAS Priority Deployment Project [KGZD-EW-103-2] 

主　　题：affine transforms convergence of numerical methods correlation theory echo suppression maximum likelihood estimation minimisation APA Huber objective function minimisation convergence correlation method cost function echo cancellation error signal far-end input signal robust Huber M-estimator based proportionate affine projection algorithm variable cutoff updating 

摘      要：A novel Huber M-estimator based proportionate affine projection algorithm (APA) is proposed for echo cancellation. The Huber objective function is minimised as the cost function and results in Huber M-estimator based APA. Moreover, the cutoff value of Huber objective function is updated according to the correlation between the error signal and the far-end input signal. It is shown that the proposed algorithm can achieve faster convergence and better robustness against double-talk than conventional robust algorithms.