共查询到18条相似文献,搜索用时 531 毫秒
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为研究地震子波相位对反射系数序列反演的影响,在自回归滑动平均(ARMA)模型描述子波的基础上,提出采用z域对称映射ARMA模型零极点的方法构造了一系列相同振幅谱、不同相位谱的地震子波,并结合谱除法对人工合成地震记录进行反射系数序列反演.理论分析表明,子波相位估计不准时反射系数序列反演结果中残留一个纯相位滤波器,该纯相位滤波器的相位谱为真实子波和构造子波的相位谱之差.采用丰度和变分作为评价方法,在反演结果中确定出真实的或准确的反射系数序列.仿真实验和实际数据处理结果也验证了子波相位对反射系数序列反演的影响规律和评价方法的有效性,为进一步提高反射系数序列反演结果精度指明了研究方向. 相似文献
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基于 trous小波变换的噪声模型,通过小波变换与统计显著性检验模型的有机结合,产生了数据图象结构的多尺度支撑表示.这一表示不仅给出了数据结构在不同尺度的形状和位置,而且剔除了噪声对结构的影响.由于相应的算法对数据结构的先验假设要求不高,故这一方法适用于分析结构复杂的数据.本文将该思路用于地震空间活动性的研究,重点探讨了如何识别并描述不同尺度地震空间活动性异常的方法.以我国西南地区松潘、黄龙、龙陵、盐源等典型地震序列为例,分析了不同尺度地震空间活动性异常的结构特征.研究表明,地震活动性异常的多尺度空间结构与强震震中之间存在一定的关系,而松潘序列前震活动性异常的时空演化也表现出一定的规律. 相似文献
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针对地震勘探资料湮没在随机噪声中的微弱同相轴问题提出基于混沌理论的混沌振子检测算法. 利用修正的Duffing_Holmes方程建立检测微弱同相轴的混沌振子系统,之后经过对同相轴的扫描处理,构成新子波等时间间隔序列W(t),与此同时对随机噪声也进行相同的截断. 截断的随机噪声在混沌振子系统中可以具有与周期信号相同的表现;经过大量仿真实验确定出满足通常地震勘探子波延续时间的使混沌振子检测子波不呈现周期相态的随机噪声截断时间范围. 选用与松辽盆地T1、T2反射层类似的子波函数并构成待检微弱周期信号,经过MATLAB仿真试验成功地检测出该弱信号,信噪比达到约-103dB. 相似文献
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地球物理信号中普遍含有噪声,消除噪声是地球物理信号处理中的关键技术之一.奇异功率谱分析(SSA)是在状态空间(又称相空间)中研究(系统)动力学、非线性科学与混沌现象的方法.本文在状态空间中通过SSA分解,研究、应用地球物理序列的尺度不变性进行多维分形滤波:通过在状态空间的SSA分解,构造了经验正交函数系(EOF);在EOF子空间中定义了两种尺度与测度后,发现了两种测度与尺度皆在多个尺度范围内存在尺度不变性;利用这种尺度~测度的尺度不变性,设计、实现了多维分形奇异功率谱(MSSA)滤波模型;处理解释了大洋钻探(ODP)1143A孔岩芯自然反射性(NGR)资料;Fourier功率谱分析结果证明,MSSA能有效地压制噪声,提取有用信号.研究得出,嵌入维数对MSSA基本无影响(小于1/1000),多维分形滤波器(MSSA)能有效压制噪声或提取有用信号. 相似文献
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地球物理信号中普遍含有噪声,消除噪声是地球物理信号处理中的关键技术之一.奇异功率谱分析(SSA)是在状态空间(又称相空间)中研究(系统)动力学、非线性科学与混沌现象的方法.本文在状态空间中通过SSA分解,研究、应用地球物理序列的尺度不变性进行多维分形滤波:通过在状态空间的SSA分解,构造了经验正交函数系(EOF);在EOF子空间中定义了两种尺度与测度后,发现了两种测度与尺度皆在多个尺度范围内存在尺度不变性;利用这种尺度~测度的尺度不变性,设计、实现了多维分形奇异功率谱(MSSA)滤波模型;处理解释了大洋钻探(ODP)1143A孔岩芯自然反射性(NGR)资料;Fourier功率谱分析结果证明,MSSA能有效地压制噪声,提取有用信号.研究得出,嵌入维数对MSSA基本无影响(小于1/1000),多维分形滤波器(MSSA)能有效压制噪声或提取有用信号. 相似文献
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为了提高多时相遥感图像变化检测的精确度和运算效率,本文提出了一种基于Contourlet变换和独立分量分析(ICA-Independent component analysis)的变化检测算法.利用Contourlet变换多尺度、多方向性和各向异性等性质,对图像数据进行多尺度分解,再对分解后的数据进行独立分量分析,利用改进的基于牛顿迭代的固定点ICA算法分离出互相独立的数据分量,然后将分离后的数据分量转变成图像分量,最终对变化图像分量经阈值分割实现变化检测.实验结果表明,与现有的基于PCA、基于ICA、基于小波变换与ICA三种变化检测算法相比,本文算法能有效地分离出变化信息,减少了计算的复杂性,得到的变化图像具有更高的精确度,且对背景有较强的稳健性. 相似文献
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基于连续小波变换的大地电磁信号谱估计方法 总被引:16,自引:5,他引:11
在基于连续小波变换的大地电磁信号谱估计方法中 ,通过引入整体平均、小波系数收缩和显著性检验等统计技术 ,以提高谱估计的精度 .文中同时讨论了连续小波变换中各种参数的选取问题 ,给出了Morlet小波函数中尺度与傅里叶频率之间转换的经验公式 ,并给出了谱估计的具体算法 .结果表明 ,本文方法可有效压制较强的白噪声和局部相关噪声 .与FFT谱估计方法相比 ,该方法大大降低了对信号记录长度的要求 ,因而对大地电磁信号的处理有实际意义 . 相似文献
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Xinjun Tu Qiang Zhang Vijay P. Singh Xiaohong Chen Chun-Ling Liu Shao-Bo Wang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(6):823-834
Due to the influence of climate change and human activities, more and more regions around the world are nowadays facing serious water shortages. This is particularly so with the Guangdong province, an economically prosperous region in China. This study aims at understanding the abrupt behavior of hydrological processes by analyzing monthly precipitation series from 257 rain gauging stations and monthly streamflow series from 25 hydrological stations using the likelihood ratio statistic and schwarz information criterion (SIC). The underlying causes of the changing properties of hydrological processes are investigated by analyzing precipitation changes and information of water reservoirs. It is found that (1) streamflow series in dry season seems to exhibit abrupt changes when compared to that in the flood season; (2) abrupt changes in the values of mean and variance of hydrological variables in the dry season are more common than those in the streamflow series in the flood season, which implies that streamflow in the dry season is more sensitive to human activities and climate change than that in the flood season; (3) no change points are identified in the annual precipitation and precipitation series in the flood season. Annual streamflow and streamflow in the flood season exhibit no abrupt changes, showing the influence of precipitation on streamflow changes in the flood season. However, streamflow changes in the dry season seem to be heavily influenced by hydrological regulations of water reservoirs. The results of this study are of practical importance for regional water resource management in the Guangdong province. 相似文献
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Weak Seismic Signal Extraction Based on the Curvelet Transform 总被引:1,自引:1,他引:0
Seismic signal denoising is a key step in seismic data processing. Airgun signals are easy to be interfered with by noise when it travels a long distance due to the weak energy of active source signal of the airgun. Aiming to solve this problem, and considering that the conventional Curvelet transform threshold processing method does not use the seismic spectrum information, we independently process the Curvelet scale layer corresponding to valid data based on the characteristics of the Curvelet transform of multi-scale, multi-direction and capable of expressing the sparse seismic signals in order to fully excavate the information features. Combined with the Curvelet adaptive threshold denoising the algorithm, we apply the Curvelet transform to denoising seismic signals while retaining the weak information in the signal as much as possible. The simulation experiments show that the improved threshold denoising method based on Curvelet transform is superior to the frequency domain filtering, wavelet denoising and traditional Curvelet denoising method in detailed information extraction and signal denoising of low SNR signals. The calculation accuracy of the relative wave velocity variation of underground medium is improved. 相似文献
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Introduction The accurate gradual change style seismic phases identification is an older new question for discussion. Wavelet transform has good localization properties in time-frequency domain, and is a effective tool to analyze seismic signal which has been applied to detection of many kinds of signal, picture processing and other fields. When a kind of new signal stack up another kind of signal, more high frequency signal components will happen at onset time of new signal. Based on the wave… 相似文献
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