Wavelet denoising with evolutionary algorithms

被引:23
作者
da Silva, ARF [1 ]
机构
[1] Univ Nova Lisboa, P-1200 Lisbon, Portugal
关键词
signal denoising; wavelet packet thresholding; best-basis representations; evolutionary optimization;
D O I
10.1016/j.dsp.2004.11.003
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 [电气工程]; 0809 [电子科学与技术];
摘要
In recent years several wavelet thresholding schemes for denoising have been proposed, However, thresholding rules depend heavily on the choice of the parameters. Wavelet thresholding rules are typically nonlinear, leading to nonconvex target functions. In this paper, we present an evolutionary computation approach for parameter elicitation in penalized wavelet models. We be-in with parameter models for global hard- and soft-thresholding. Then, we extend the methodology for parameter elicitation in two directions: block thresholding and best-basis denoising. The proposed evolutionary approach enables the joint optimization of wavelet basis selection and thresholding parameters for signal denoising. Numerical simulations are used to illustrate the proposed methodology and compare the behavior of the various denoising procedures. (c) 2005 Elsevier Inc. All rights reserved.
引用
收藏
页码:382 / 399
页数:18
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