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- 2018
连续重力观测异常模式的多分辨率识别算法
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Abstract:
在小波多孔算法的基础上，提出了一种综合信号频率信息和幅值信息的连续重力观测数据多分辨率异常模式识别算法，利用小波分解得到高频区域的能量作为频率指标，与幅值相结合，对信号及其多孔小波分解结果进行多分辨率异常模式识别。利用模拟数据和实际超导重力观测数据对算法的有效性进行了验证，结果表明，该算法能够准确地在带有噪声的信号中识别模拟数据的异常模式，可应用于连续重力观测台网数据分析处理，对于提升台网观测数据质量以及地震预测等实际应用都具有重要意义。用此方法分析拉萨和武汉的3台超导重力仪2015-04-25尼泊尔地震前一天的秒采样数据后，得到一段27 min的在频率指标上有超过90%相似性的异常模式，这一结果的更深层次物理解释仍需要进一步研究
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