首页 | 本学科首页   官方微博 | 高级检索  
     


An adaptive approach for the identification of improper complex signals
Authors:Beth Jelfs  Danilo P. MandicScott C. Douglas
Affiliation:a Department of Electrical & Electronic Engineering, Imperial College London, London SW7 2BT, UK
b Department of Electrical Engineering, Southern Methodist University, Dallas, TX 75275, USA
Abstract:A real-time approach for the identification of second-order noncircularity (improperness) of complex valued signals is introduced. This is achieved based on a convex combination of a standard and widely linear complex adaptive filter, trained by the corresponding complex least mean square (CLMS) and augmented CLMS (ACLMS) algorithms. By providing a rigorous account of widely linear autoregressive modelling the analysis shows that the monitoring of the evolution of the adaptive convex mixing parameter within this structure makes it possible to both detect and track the complex improperness in real time, unlike current methods which are block based and static. The existence and uniqueness of the solution are illustrated through the analysis of the convergence of the convex mixing parameter. The analysis is supported by simulations on representative datasets, for a range of both proper and improper inputs.
Keywords:Complex circularity   Widely linear autoregressive modelling   Collaborative filter   Augmented complex least mean square (ACLMS)   Improper complex signals   Wind modelling
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号