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《Chinese Journal of Geophysics》 2001-02
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DONG EN QING\ LIU GUI ZHONG\ ZHANG ZONG PING (School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an 710049, China)  
A new approach of adaptive Kalman filtering deconvolution (AKFD) via dyadic wavelet transform is proposed. To the computing complexity of the approach, a fast implementation technique is proposed. The AKFD via dyadic wavelet transform discards the assumption of stationarity of signals in predictive deconvolution, and solves the problem of improving resolution at the price of decreasing signal to noise rate (SNR) obviously, consequently it has a better ability of resistance noise. Suppressing false reflections and improving resolution in dyadic wavelet transform domain is better than that in time domain. At the same time, the approach also overcomes the drawback of increasing the low frequency component of AKFD in time domain. The fast implementation technique makes use of the assumption of local stationary for 2D seismic data. The technique reduces the calculation amount of the adaptive predictive operators by calculating an adaptive predictive operator in each segment, and then applying the algorithm of spline interpolation to interpolate in transverse and in portrait. A great deal of experiments indicates that the computing speed can be increased hundreds times, and the original calculation effect is still maintained.
【Fund】: 国家自然科学基金!资助项目 ( 69872 0 3 0 )
【CateGory Index】: P631.4
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