应用于地震数据去卷的自校正白噪声估值器
Self-Tuning White Noise Estimators with Application of Seismic Data Deconvolution
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摘要: 本文把地震数据去卷问题处理为估计带观测噪声的ARMA模型的白噪声问题,应用时间 序列分析方法提出了不同于Mendel的新的稳态最优白噪声估值器,文章基于两个ARMA新 息模型的在线辨识,进一步给出了自校正白噪声估值器.Abstract: In this paper, the problem of seismic data deconvolution is treated as a problem of estimating the white noise of the ARMA model with observation noise. Using the time series analysis method, we present new steadystate optimal white noise estimators which are different from that of Mendel. Based on the on-line identification of two ARMA innovation models, the selftuning white noise estimators are further given.
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