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characteristic mapping
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    The principle of singular-value decomposition (SVD)filtering is sketched out here. Trial analysis of different typical synthetic seismograms is made to find out the major factors which influence SVD filtering effect,so that the measures for improving SVD filtering are advanced,which are dip scanning stack based on SVD,and SVD filtering parameter determination using self-organized characteristic mapping neural network.
    本文介绍了奇异值分解SVD滤波原理,并用不同的具有代表性的合成地震记录进行了试验、分析,得出了影响SVD滤波效果的主要因素,从而提出了SVD滤波的改进方法─—基于SVD的倾角扫描叠加和自组织特征映射神经网络确定SVD滤波参数。
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  特征映射
    The principle of singular-value decomposition (SVD)filtering is sketched out here. Trial analysis of different typical synthetic seismograms is made to find out the major factors which influence SVD filtering effect,so that the measures for improving SVD filtering are advanced,which are dip scanning stack based on SVD,and SVD filtering parameter determination using self-organized characteristic mapping neural network.
    本文介绍了奇异值分解SVD滤波原理,并用不同的具有代表性的合成地震记录进行了试验、分析,得出了影响SVD滤波效果的主要因素,从而提出了SVD滤波的改进方法─—基于SVD的倾角扫描叠加和自组织特征映射神经网络确定SVD滤波参数。
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  characteristic mapping
Some characteristic mapping has also been conducted showing the main parameters of water utilization, need and spatial issues regarding consumptive use of water during agricultural operations as per the seasons prevalent in India.
      
The complexity of nature must be reduced to a few significant and characteristic mapping units.
      


The principle of singular-value decomposition (SVD)filtering is sketched out here. Trial analysis of different typical synthetic seismograms is made to find out the major factors which influence SVD filtering effect,so that the measures for improving SVD filtering are advanced,which are dip scanning stack based on SVD,and SVD filtering parameter determination using self-organized characteristic mapping neural network. This method has been applied in real data processing to result in good effect.

本文介绍了奇异值分解SVD滤波原理,并用不同的具有代表性的合成地震记录进行了试验、分析,得出了影响SVD滤波效果的主要因素,从而提出了SVD滤波的改进方法─—基于SVD的倾角扫描叠加和自组织特征映射神经网络确定SVD滤波参数。将此法用于实际地震资料处理,效果明显。

 
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