信号去噪阈值参数选择的自适应退火遗传算法  

The Adaptive Annealing Genetic Algorithm for Selecting Wavelet Denoising Threshold Parameter

作　　者：黄宜军[1] 汪金友[1] 

机构地区：[1]信阳师范学院计算机系

出　　处：《测试技术学报》2006年第5期456-460,共5页Journal of Test and Measurement Technology

基　　金：教育部985工程资助项目

摘　　要：提出了一个用于小波阈值去噪中最优阈值参数选取的自适应退火遗传算法,提出一种新的自适应退火策略用于选择概率的计算以增强算法的收敛性,在交叉和变异概率的选取上也进行了自适应处理,以进一步改善算法的稳定性和收敛性.计算机仿真结果表明,该算法可稳定有效地选取最优的去噪阈值参数.It＇s very difficult to select the best wavelet denoising tnresnold, A novel auaptive a genetic algorithm is presented to solve this problem. A new adaptive annealing method is given to calculate select probability for improving the convergence of this algorithm. Cross probability and variance probability are selected adaptively for enhancing the stability and convergence of the algorithm. The simulation result shows that the best wavelet denoising threshold parameter can be chosen effectively by this algorithm.

关 键 词：小波分析 消噪 阈值 遗传算法 自适应 退火 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]