Wavelet Thresholding Denoising Based on Simplex-Simulated Annealing Algorithm
Expounding the basic theory and method of removing noises from signals with wavelet analysis, the determination of the threshold has an impact on the quality of removing noises from signals. This paper presents an new method based on generalized cross validation (GCV), it can get optimal thresholds of every wavelet subband by using the method of simplex-simulated annealing algorithm without requiring the prior knowledge of the noise variance, at the same time this method is independent of the choice of initial threshold, and it not only gets the global optimum, but also enhances searching efficiency. And then using Matlab to realize simulation of wavelet denoising by programming, the results show that the threshold in this paper is excellent compared with four threshold selection rules (Rigrsure, Sqtwolog Heursure, Minimaxi), and it gives better SNR gains and RMSE performance of denoising effects.
Xin WANG Chunhui ZHAO Jiangang RONG
Harbin Engineering University, China The 8511th Research Institute of CASIC, China
国际会议
2nd IEEE Conference on Industrial Electronics and Applications(ICIEA 2007)(第二届IEEE工业电子与应用国际会议)
哈尔滨
英文
2007-05-23（万方平台首次上网日期，不代表论文的发表时间）