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Using a sparse model to evaluate the internal structure of impulse signals

机译:使用稀疏模型评估脉冲信号的内部结构

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Impulse nature signals generated by complex geophysical systems require special methods to study their internal structure. These signals are characterized by a short duration of impulses and the variability of their structure. The use of classical spectral and time-frequency methods raises great difficulty. The authors propose a model of an impulse signal based on a sparse approximation and an algorithm for identifying a model. The algorithm is a modified matching pursuit algorithm using a physically based system of functions (dictionary). The study of modeling results consists in estimating the time-frequency characteristics of the model components. The paper gives an example of the model application on geoacoustic emission signals of a seismically active region (Kamchatka peninsula). The proposed model and approaches to the model investigation can be used for a wide range of impulse nature signals.
机译:由复杂的地球物理系统生成的脉冲自然信号需要特殊的方法来研究其内部结构。这些信号的特点是脉冲持续时间短且结构可变。经典频谱和时频方法的使用带来了很大的困难。作者提出了一种基于稀疏近似的脉冲信号模型和一种用于识别模型的算法。该算法是使用基于物理的功能系统(词典)的改进的匹配追踪算法。建模结果的研究在于估计模型组件的时频特性。本文给出了在地震活跃地区(堪察加半岛)的地声发射信号上的模型应用实例。所提出的模型和用于模型研究的方法可以用于广泛的脉冲自然信号。

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