An adaptive wavelet denoising method for the measuring system of EMP signals

Author

Lihua, Shi ; Bin, Chen ; Zhou Binhua ; Cheng, Gao

Author_Institution

EMP Lab., Nanjing Eng. Inst., China

fYear

2000

fDate

2000

Firstpage

138

Lastpage

141

Abstract

An adaptive wavelet denoising method is proposed to eliminate the noise induced by the measuring system of EMP signals. This method employs a threshold-searching strategy to select an optimal denoising threshold for a given system. Wavelet decomposition and reconstruction are combined with neural network nonlinear threshold-filtering units in the new denoising algorithm. Based on a group of training signal, the denoising threshold can be learned adaptively. The training algorithm and application examples are given in this paper

Keywords

electric field measurement; electrical engineering computing; electromagnetic pulse; learning (artificial intelligence); magnetic field measurement; neural nets; nonlinear filters; pulse measurement; wavelet transforms; EMP signals; adaptive learning; adaptive wavelet denoising method; denoising threshold; induced noise elimination; measuring system; neural network nonlinear threshold-filtering units; optimal denoising threshold; threshold-searching strategy; training signal; wavelet decomposition; wavelet reconstruction; EMP radiation effects; Independent component analysis; Neural networks; Noise measurement; Noise reduction; Signal analysis; Signal processing; Signal processing algorithms; Wavelet coefficients; Wavelet transforms;

fLanguage

English

Publisher

ieee

Conference_Titel

Environmental Electromagnetics, 2000. CEEM 2000. Proceedings. Asia-Pacific Conference on

Conference_Location

Shanghai

Print_ISBN

7-5635-0420-6

Type

conf

DOI

10.1109/CEEM.2000.853917

Filename

853917