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将地震信号分解成包含频谱互不重叠的单主周期的分量有利于地震信号的分析.分析了经验模态分解(EMD)中模态混叠的内在原因和已有的解决方法，梳理了解决模态混叠的思路框架，进而提出了一种新的基于输入递归高通滤波的EMD算法.首先用递归高通滤波器将信号预分解成频率由高到低的多个分量，实现信号的等价带通滤波，再用EMD对各带通分量按频率高低逐级递归筛分，获得完备的经验模态分量.通过合成信号和地震信号的仿真实验表明，该算法较好地克服了模态混叠，获得了频谱互不重叠的单主周期分量，并成功用于震相分离和分析，为地震信号分析提供了一种新思路. 相似文献
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An important problem in hydrologic science is understanding how river flow is influenced by rainfall properties and drainage basin characteristics. In this paper we consider one approach, the use of mass exponents, in examining the relation of river flow to rainfall and the channel network, which provides the primary conduit for transport of water to the outlet in a large basin. Mass exponents, which characterize the power-law behavior of moments as a function of scale, are ideally suited for defining scaling behavior of processes that exhibit a high degree of variability or intermittency. The main result in this paper is an expression relating the mass exponent of flow resulting from an instantaneous burst of rainfall to the mass exponents of spatial rainfall and that of the network width function. Spatial rainfall is modeled as a random multiplicative cascade and the channel network as a recursive replacement tree; these fractal models reproduce certain types of self-similar behavior seen in actual rainfall and networks. It is shown that under these modeling assumptions the scaling behavior of flow mirrors that of rainfall if rainfall is highly variable in space, and on the other hand flow mirrors the structure of the network if rainfall is not so highly variable. 相似文献
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针对利用地震道进行相对波阻抗反演中遇到的横向连续性难以保持、初始子波容错度差以及随机噪声干扰影响反演结果等问题,提出了一种基于矩阵Toeplitz稀疏分解的相对波阻抗反演方法.该方法将地震数据剖面的Toeplitz稀疏分解问题分解为两个子反演问题,其一以Toeplitz子波矩阵元素为待反演的参数,用Fused Lasso方法求解,可保证子波具有紧支集且是光滑的;其二以稀疏反射系数矩阵元素为待反演参数,用基于回溯的快速萎缩阈值迭代算法求解,大大降低了目标函数中参数选择的难度.通过交替迭代求解上述两个子反演问题可将地震数据剖面因式分解为一个Toeplitz子波矩阵和一个稀疏反射系数矩阵;然后由反射系数矩阵递推反演可以得到高分辨率的相对波阻抗剖面;利用测井资料加入低频分量后,也可得到高分辨率的绝对波阻抗剖面.Marmousi2模型生成的合成记录算例和实际地震资料算例均表明:本文方法可以从带限地震数据中有效地反演相对波阻抗,反演结果分辨率高并且能够很好地保持地震数据的横向连续性;即使在初始估计子波存在误差和地震数据被随机噪声污染的情况下也能取得较好的效果. 相似文献
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Chang-bin Li Jia-guo Qi Lin-shan Yang Wen-jin Yang Gao-feng Zhu Shuai-bing Wang 《山地科学学报》2014,11(4):884-895
The study of snow and ice melt （SIM） is important in water-scarce arid regions for the assessment of water supply and quality. These studies involve unique difficulties, especially in the calibration of hydro-models because there is no direct way to continuously measure the SIM at hydrostations. The recursive digital filter （RDF） and the isotopic hydro-geochemical method （IHM） were coupled to separate the SIM from eight observed series of alpine streamflows in northwestern China. Validation of the calibrated methods suggested a good capture of the SIM characteristics with fair accuracy in both space and time. Applications of the coupled methods in the upper reaches of the Hei River Basin （HRB） suggested a double peak curve of the SIM fraction to streamflow for the multi-component recharged （MCR） rivers, while a single peak curve was suggested for the rainfall-dominant recharged （RDR） rivers. Given inter-annual statistics of the separation, both types of the alpine rivers have experienced an obvious decrease of SIM since 196os. In the past 10 years, the SIM in the two types of rivers has risen to the levels of the 1970s, but has remained lower than the level of the 1960s. The study provided a considerable evidence to quantify the alpine SIMbased on the separation of observed data series at gauge stations. Application of the coupled method could be helpful in the calibration and validation of SIM-related hydro-models in alpine regions. 相似文献
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Hai Huang 《International journal of geographical information science》2013,27(12):2075-2094
This paper presents an original approach to dynamic anomalous behavior detection in individual trajectory using a recursive Bayesian filter. The anomalous pattern detection is of great interest for navigation, driver assistance systems, surveillance as well as crisis management. In this work, we focus on the GPS trajectories of automobiles finding where the driver’s behavior shows anomalies. Such anomalous behaviors can happen in many cases, especially when the driver encounters orientation problems, i.e., taking a wrong turn, performing a detour, or losing the way. First, three high-level features, i.e., turns and their density, detour factor, and route repetition are extracted from the given trajectory geometry, for which a long-term perspective is required to observe data sequences of a significant length instead of individual time stamps. We therefore employ high-order Markov chains with a ‘dynamic memory’ to model the trajectory integrating these long-term features. The Markov model is processed by a proposed recursive Bayesian filter to infer an optimal probability distribution of the potential anomalous driving behaviors dynamically over time. The filter performs unsupervised detection in single trajectories based on local features only. No training process is required to characterize the anomalous behaviors. By analyzing the detection results of individual trajectories, collective behaviors can be derived indicating traffic issues such as congestions and turn restrictions. Experiments are performed on volunteered geographic information (VGI) data, self-acquired trajectories, and open trajectory datasets to demonstrate the potential of the proposed approach. 相似文献
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This paper presents a novel intelligent fuzzy weighted input estimation method which effiviently and robustly estimates the unknown ground motion accelerations. The new input estimation method includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. By directly synthesizing the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The excellent performace of this inverse method is demonstrated by solving the earthquake-excitation estimation problem, and the proposed algorithm is compared by alternating between the constant and adaptive weighting factors. The results reveal that this method has the properties of better target tracking capability and more effective noise reduction. 相似文献
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This article extends the earlier work (Haavisto et al. 2008. Optical spectrum based measurement of flotation slurry contents. Int. J. Miner. Process. 88 (3–4), 80–88), where visible and near-infrared (VNIR) reflectance spectroscopy was used together with an X-ray fluorescence (XRF) analyzer to improve the assaying of zinc flotation concentrate. Especially the sampling interval of the assay could be drastically reduced by the presented approach. In this study, a multichannel VNIR spectrum analyzer is utilized to measure the spectrum of the seven most important slurry lines in copper and zinc flotation circuits. Recursive data-based modeling is applied to the VNIR spectrum data and XRF assays to calculate and adaptively maintain the calibration model. The accuracy of the VNIR assays is evaluated in all the lines, and the benefits of the obtained high frequency assays in detecting oscillations and sudden grade changes are demonstrated. 相似文献
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李邦宪 《成都信息工程学院学报》1989,(2)
本文针对经典多层递阶方法所存在的缺陷,提出了一种改进方案—带有周期分量的多层递阶预报模型,它利用时间序列的显著周期分量取代原模型中的自回归部分,使之既考虑到各种物理因子的主导作用,又较好地反映了气象要素自身的周期性变化规律,因而预报效果较为稳定。 相似文献