In this paper we proposed a new method for seismic wavelet estimation based on the genetic algorithms.
本文基于遗传算法提出了一个新的地震子波估计方法。
The method of the robustness seismic wavelet estimation using the maximum likelihood deconvolution are discussed in the paper.
利用极大似然反褶积提取鲁棒性地震子波的方法进行了研究，并讨论了极大似然反褶积的稳健性。
Recently, the statistical methods of seismic wavelet estimation achieved comprehensive application in real seismic data processing.
近年来，统计地震性子波估计技术在实际地震数据处理中得到了广泛应用。
This paper studies a statistical seismic wavelet estimation method, which based on higher order statistics and the hybrid ant colony algorithm.
本文重点研究了统计性方法中，基于高阶统计量及混合蚁群算法的地震子波估计方法。
The model test results of seismic wavelet estimation show that the method is more efficient than that only use stochastic optimization algorithm.
通过对地震记录子波估计的理论模型试验，结果表明这种混沌的优化算法比单一的随机优化方法具有很好的实际效果和应用前景。
The novel method of Estimation and extraction of seismic Wavelet-Higher order cumulants is presented in this thesis at first.
本文首先引出地震子波估计和外推的最新方法—高阶累积量法。
Wavelet processing, in which wavelet estimation is essential, is an effective technique for improving the resolution of seismic data.
子波处理技术是提高地震资料分辨率的一种有效方法，其关键在于获得准确的子波估计。
The estimation of the seismic wavelet has a very important significance for improving the resolution and signal-to-noise of seismic data, and it is a long-term research in seismic data processing.
地震子波估计对于提高地震资料数据的分辨率、信噪比有着极为重要的意义，是国内外地震信号处理中长期研究的重要课题。
Wavelet Processing is an important technique used to improve the resolution of seismic data, in which the key is wavelet estimation.
子波处理是提高地震资料分辨的一个重要手段，该技术的关键是地震子波的估计。
Wavelet Processing is an important technique used to improve the resolution of seismic data, in which the key is wavelet estimation.
子波处理是提高地震资料分辨的一个重要手段，该技术的关键是地震子波的估计。
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