Bias-Compensated LMS Algorithm for Sparse Systems over Adaptive Network

作     者：Wenxuan Han Lijuan Jia Shunshoku Kanae Zijiang Yang 

作者单位：School of Information and ElectronicsBeijing Institute of Technology Fukui University of Technology Ibaraki University 

会议名称：《第36届中国控制会议》

会议届次：36

主办单位：Dalian University of Technology;Systems Engineering Society of China (SESC);Technical Committee on Control Theory (TCCT), Chinese Association of Automation (CAA)

会议日期：2017年

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

关 键 词：Bias-compensation least mean squares sparse system diffusion networks adaptive networks 

摘      要：We propose bias-compensated algorithms based on the RZA-LMS algorithm and diffusion RZA-LMS *** proposed algorithms improve the accuracy of estimation under the situation that input of the adaptive filter contains *** methods of the input noise’ variance are given for implementing our single-node and diffusion biascompensated *** results show that the proposed algorithms have better accuracy than algorithms without bias-compensation and the estimation results are unbiased under different noise levels.