Title :
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
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;
Conference_Titel :
Environmental Electromagnetics, 2000. CEEM 2000. Proceedings. Asia-Pacific Conference on
Conference_Location :
Shanghai
Print_ISBN :
7-5635-0420-6
DOI :
10.1109/CEEM.2000.853917
