Matching pursuits with undercomplete dictionary
Matching pursuit (MP) is an iterative algorithm for signal representation which is applied widely to compression,feature extraction,signal denoising,and more.During last decades,main attention about the algorithm has been focused on the signal decomposition with respect to a complete or overcomplete dictionary.However,in this paper,we extend results by Mallat and Zhang about MP with overcomplete dictionaries to undercomplete one,and consider MP with a undercomplete dictionary.We investigate theoretically properties of undercomplete dictionary and demonstrate its binary partition ability to signal space.Furthermore,we derive bounds on the residual energy of any signal by MP with a undercomplete dictionary.Numerical simulations based on synthetic data are provided.Results show a promising pattern classification ability held by the MP with a undercomplete dictionary..
Sparse representation matching pursuits undercomplete expansions pattern classification
Dang-wei Wang Xiao-yan Ma
Wuhan Radar Academy Wuhan 430019,P.R.China
国际会议
9th International Conference on Signal Processing(第九届国际信号处理学术会议)(ICSP08)
北京
英文
2008-10-26（万方平台首次上网日期，不代表论文的发表时间）