[1] Wu Feiyun, Tong Feng. Non-uniform norm constraint LMS algorithm for sparse system identification [J]. IEEE Communications Letters, 2013, 17(2): 385-388.[2] Kalouptsidis N, Mileounis G, Babadi B, et al. Adaptive algorithms for sparse system identification [J]. Signal Processing, 2011, 91(8): 1910-1919.[3] Zhao Shengkui, Zhihong Man, Suiyang Khoo, et al. Variable step-size LMS algorithm with a quotient form [J]. Signal processing, 2009, 89(1): 67-76.[4] 田福庆, 罗荣, 李克玉, 等. 基于改进的双曲正切函数变步长LMS算法[J]. 系统工程与电子技术, 2012, 34(9): 1758-1706. Tian Fuqing, Luo Rong, Li Keyu, et al. New variable step-size LMS algorithm based on modified hyperbolic tangent function [J]. Systems Engineering and Electronics, 2012, 34(9): 1758-1706.[5] Costa, Márcio Holsbach, José Carlos Moreira Bermudez. A noise resilient variable step-size LMS algorithm [J]. Signal Processing, 2008, 88(3): 733-748.[6] Gu Yuantao, Jin Jian, and Mei Shunliang. l0 norm constraint LMS algorithm for sparse system identification [J]. IEEE Signal Processing Letters, 2009, 16(9): 774-777.[7] Su Guolong, Jin Jian, Gu Yuantao, et al. Performance analysis of l0 norm constraint least mean square algorithm [J]. IEEE Transactions on Signal Processing, 2012, 60(5): 2223-2235.[8] 曲庆, 金坚, 谷源涛. 用于稀疏系统辨识的改进l0_LMS算法[J]. 电子与信息学报, 2011, 33(3): 604-609. Qu Qing, Jin Jian, Gu Yuantao. An improved l0_LMS algorithm for sparse system identification [J]. 2011, 33(3): 604-609.[9] Jin Jian, Qu Qing, Gu Yuantao. Robust zero-point attraction least mean square algorithm on near sparse system identification [J]. IET Signal Processing, 2013, 7(3): 210-218. |