Research of wavelet threshold de-noising method based on Particle Swarm Optimization

doi:10.3778/j.issn.1002-8331.2009.31.036

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (31): 122-124.DOI: 10.3778/j.issn.1002-8331.2009.31.036

• 数据库、信号与信息处理 • Previous Articles Next Articles

Research of wavelet threshold de-noising method based on Particle Swarm Optimization

GUO Xiao-xia，YANG Hui-zhong

School of Communication & Control Engineering，Jiangnan University，Wuxi，Jiangsu 214122，China

Received:2008-06-16 Revised:2008-10-12 Online:2009-11-01 Published:2009-11-01
Contact: GUO Xiao-xia

基于粒子群优化算法的小波阈值去噪方法研究

郭晓霞，杨慧中

江南大学通信与控制工程学院，江苏无锡 214122

通讯作者: 郭晓霞

Abstract

Abstract: After studying the characteristics of Particle Swarm Optimization，Particle Swarm Optimization is used in wavelet domain to optimize the thresholds，and garrote shrinkage function is used to process wavelet decomposition coefficients，which overcome the shortcoming of discontinuity of hard-threshold and decreased the fixed bias of soft-threshold.The simulation results show that this new method has better de-noising effects than traditional methods.

Key words: Particle Swarm Optimization, threshold de-noising, threshold function, Signal to Noise Ratio（SNR）

摘要： 研究粒子群优化算法的特性，将其应用于小波域，对阈值进行寻优，并使用garrote阈值函数量化小波分解系数，而garrote阈值函数既克服了硬阈值函数的不连续性，也减小了软阈值函数存在的恒定偏差。实验仿真结果表明，提出的方法较传统方法具有更好的去噪效果。

关键词: 粒子群优化算法, 阈值去噪, 阈值函数, 信噪比

CLC Number:

TP391

GUO Xiao-xia，YANG Hui-zhong. Research of wavelet threshold de-noising method based on Particle Swarm Optimization[J]. Computer Engineering and Applications, 2009, 45(31): 122-124.

郭晓霞，杨慧中. 基于粒子群优化算法的小波阈值去噪方法研究[J]. 计算机工程与应用, 2009, 45(31): 122-124.

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Research of wavelet threshold de-noising method based on Particle Swarm Optimization

基于粒子群优化算法的小波阈值去噪方法研究

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