SINGULARITY DETECTION OF NOISY SIGNALS BASED ON TWO WAVELET DENOISING ALGORITHMS
As the inevitable noises exist in actual application,the common method (MTMM) gets unacceptable result of singularity detection.In order to get more accurate singularity detection,wavelet transform shrinkage and spatially selective noise filtration methods are respectively utilized to denoise the corrupted signals.Then,the wavelet transform are applied to the two independent preprocessing signals,following that the modulus maxima are extracted for them.Based on the differences of modulus maxima dominated by noise and true signal,modulus maxima lines are picked up for the two disrelated sources.Meanwhile a proper fused and weighted manner is adapted to obtain reliable modulus maxima lines,which are directly corresponding to numbers and positions of singular points.Finally,several simulation experiments validate that the proposed algorithm obtains acceptable result of singularity detections for noisy signal,and achieves better performance over other two methods in noisy condition.
Singularity detection noisy signals WTMM wavelet transform shrinkage spatially selective noise filtration
Yan Xingwei Lu Dawei Ou Jianping Zhang Jun Wan Jianwei
School of Electronic Science and Engineering,National University of Defense Technology,Changsha,China
国际会议
北京
英文
69-74
2013-04-27（万方平台首次上网日期，不代表论文的发表时间）