共查询到18条相似文献，搜索用时 640 毫秒
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非负矩阵分解方法在水系沉积物地球化学数据处理中应用 总被引：1，自引：0，他引：1
鉴于水系沉积物地球化学数据可以表示为非负矩阵,这使得利用非负矩阵分解(NMF)方法处理该类数据成为可能.介绍了非负矩阵分解方法的基本原理和方法,讨论了基于非负矩阵分解方法处理水系沉积物地球化学数据的可能和效果.以个旧水系沉积物地球化学数据为例,运用NMF方法和主成分分析(PCA)方法对其进行异常分析,并对这两种方法的处理结果进行了比较,发现NMF方法对于处理水系沉积物地球化学数据是一种有效的方法.尽管这两种方法各自有其优越性,但就本实例数据而言,NMF方法优于PCA方法. 相似文献
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非负矩阵分解是一种提取图像原始信息局部特征的新方法,第二代Curvelet变换是一种效果较好的多尺度变换分析方法。结合两者特征提出一种基于NMF和Curvelet的遥感图像的融合方法,首先对已配准的多光谱图像和全色图像进行Curevelet分解,得到各层系数（Coarse、Detail和Fine尺度层）。然后对Coarse尺度层（低频系数）进行NMF分解,提取出包含特征基的低频系数;对Detail和Fine尺度层（高频系数）采用方差为测度参数进行邻域融合。最后进行Curevelet逆变换得到融合图像。实验结果表明,该方法的融合图像能较好地保留光谱信息,并在空间细节信息上得到改善,优于小波方法、Curvelet等方法。 相似文献
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所谓近似对称矩阵是指矩阵中仅有极少一部分元素是非对称的,在将对角线以上的非对称元素用其对角线以下的对称元素替代后,该矩阵就变成了一个对称矩阵。在求解非线性连续介质力学问题时常常会遇到近似非对称矩阵。基于Sherman-Morrison定理,给出了一种新的近似非对称矩阵的分解算法。在确保数值稳定性的前提下,无论在求解效率还是在内存开销方面新算法都优于一般的非对称稀疏矩阵的求解器,且仅需对传统的基于LDLT分解的求解器略做修改,即可开发出适应于对称和非对称稀疏矩阵的求解器。最后用一个摩擦接触算例,显示了新算法的优越性。 相似文献
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前言矩阵分解的分层解释方法早在七十年代末就有介绍,但它仅把对称正定带型矩的乔累斯基分解算法直接应用在分层解释中的线性方程组求解上。因此,无论是算法的简易程度,还是运算的工作量都不易被人们接受,它仅作为一种原理性的探讨出现在刊物上。近几年来,笔者在探讨矩阵分解时发现:分解后的系数半带矩阵并非无序可循,而在该矩阵的半带宽内,每相邻行的元素随着行号的加大将趋于相同。因此,我们在矩阵的分解计算中可大大简化矩阵,去掉不必要的重复计算,也不必采用文献所介绍 相似文献
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井地直流电法三维数值模拟中若干问题研究 总被引：3，自引：0，他引：3
讨论了地下垂直线源分段计算和场叠加的方法,并实现了在套管上供直流电的三维数值模拟。讨论了大型容量矩阵的压缩存储方式,采用数组和结构体相结合的方法实现容量矩阵的一维链表式压缩存储。在求解超大型稀疏线形方程组时引入不完全Cholesky分解稳定化的双共轭梯度算法(ICBG),通过与均匀半空间垂直线源解析解的对比,证明了该算法是准确可靠的。 相似文献
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基于奇异值分解法的含量-面积法对化探异常的确定 总被引：1，自引：0，他引：1
地球化学场的数据通常具有分形的特征。应用奇异值分解方法对元素含量数据矩阵进行分解,对奇异值进行分形统计,得到了分形模型。重建元素含量的数据矩阵。然后利用含量-面积的分形方法对重建后的数据矩阵进行分形处理。使用MAPGIS软件进行统计分析,得出研究地区元素的异常下限,做出元素异常分布图,并与该地区已知矿点的分布图进行叠加分析,预测潜在的成矿区。 相似文献
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在许多有限元、有限差分的应用中,待解方程组的系数矩阵是大型稀疏带状阵,方程组的求解一般使用迭代法.与其它存储方式相比,压缩对角存储由于不存矩阵元素的行列索引,对内存的使用最为节省.使用压缩对角存储,沿对角线操作可以完成高效的矩阵—向量乘.由于在以往的文献中,没有提及按行、列操作的算法,压缩对角存储的应用范围受到一定的限制.用行、列、对角版的矩阵—向量乘代表普通意义的行、列、对角方向操作模式,通过等价矩阵推导和伪代码,给出了一个包括按行、列操作算法在内的应用框架.这里运用C语言实现不完全Cholesky分解共轭梯度法解方程,阐述了如何在实际编程中使用这个算法框架.经理论与实验分析表明,对角压缩存储应用于框架中是高效的,因为与使用常用的一维行索引存储格式所编程序相比,同样迭代次数的耗时减少了约25％. 相似文献
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Progressive evolution of whole‐rock composition during metamorphism revealed by multivariate statistical analyses 
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下载免费PDF全文 Kenta Yoshida Tatsu Kuwatani Takao Hirajima Hikaru Iwamori Shotaro Akaho 《Journal of Metamorphic Geology》2018,36(1):41-54
The geochemical evolution of metamorphic rocks during subduction‐related metamorphism is described on the basis of multivariate statistical analyses. The studied data set comprises a series of mapped metamorphic rocks collected from the Sanbagawa metamorphic belt in central Shikoku, Japan, where metamorphic conditions range from the pumpellyite–actinolite to epidote–amphibolite facies. Recent progress in computational and information science provides a number of algorithms capable of revealing structures in large data sets. This study applies k‐means cluster analysis (KCA) and non‐negative matrix factorization (NMF) to a series of metapelites, which is the main lithotype of the Sanbagawa metamorphic belt. KCA describes the structures of the high‐dimensional data, while NMF provides end‐member decomposition which can be useful for evaluating the spatial distribution of continuous compositional trends. The analysed data set, derived from previously published work, contains 296 samples for which 14 elements (Si, Ti, Al, Fe, Mn, Mg, Ca, Na, K, P, Rb, Sr, Zr and Ba) have been analysed. The KCA and NMF analyses indicate five clusters and four end‐members, respectively, successfully explaining compositional variations within the data set. KCA indicates that the chemical compositions of metapelite samples from the western (Besshi) part of the sampled area differ significantly from those in the east (Asemigawa). In the west, clusters show a good correlation with the metamorphic grade. With increasing metamorphic grade, there are decreases in SiO2 and Na2O and increases in other components. However, the compositional change with metamorphic grade is less obvious in the eastern area. End‐member decomposition using NMF revealed that the evolutional change of whole‐rock composition, as correlated with metamorphic grade, approximates a stoichiometric increase of a garnet‐like component in the whole‐rock composition, possibly due to the precipitation of garnet and effusion of other components during progressive dehydration. Thermodynamic modelling of the evolution of the whole‐rock composition yielded the following results: (1) the whole‐rock composition at lower metamorphic grade favours the preferential crystallization of garnet under the conditions of the garnet zone, with biotite becoming stable together with garnet in higher‐grade rock compositions under the same P–T conditions; (2) with higher‐grade whole‐rock compositions, more H2O is retained. These results provide insight into the mechanism suppressing dehydration under high‐P metamorphic conditions. This mechanism should be considered in forward modelling of the fluid cycle in subduction zones, although such a quantitative model has yet to be developed. 相似文献
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抛物Radon变换法(Parabolic Radon Transform)在地震资料处理中有广泛的应用。PRT可对不同频率的地震数据解耦处理,这一特点使得抛物Radon变换的计算效率比双曲Radon变换有数量级上的提高。在频率域求解时,需要对每一个频率成份求解同样大小的线性方程组。求解抛物Radon正变换的计算方法主要有Levinson递推法、共轭梯度法、Cholesky分解法和直接矩阵求逆法。最小平方抛物Radon正变换所形成的矩阵具有Toeplitz结构,可采用Levinson递推法进行计算。高分辨率抛物Radon正变换所形成矩阵的Toeplitz结构被破坏,一般采用共轭梯度法或Cholesky分解法进行求解。这里详细推导了复Toeplitz矩阵的Levinson递推算法,并分别对求解方程的四种方法进行了讨论,最后给出抛物Radon正变换求解的数值算例,并对所给出的四种方程求解方法的计算效率及计算精度进行了对比。 相似文献
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全波形反演不仅利用相位和振幅信息,还利用波形的细节变化,具有刻画模型精确细节的能力.在对稀疏矩阵直接LU分解求解的基础上,采用梯度预处理方法对声波介质速度模型进行了反射波全波形反演.采用误差反向传播算法计算目标函数梯度以及伪Hessian矩阵的对角线元素来做梯度预处理.数值模型的实验结果表明,利用有效的频率段便能反演出分辨率较高的速度结构,用低频反演出的结果作为高频反演的初始模型,减少了解的非唯一性.二维高斯光滑初始模型提供了有利的低频信息,得到较好的反演结果.伪Hessian矩阵的预处理吸收了高斯牛顿法的二次收敛优势,在不增加计算量的前提下,加快收敛速度. 相似文献
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Preconditioned projection (or conjugate gradient like) methods are increasingly used for the accurate and efficient solution to finite element (FE) coupled consolidation equations. Theory indicates that preliminary row/column scaling does not affect the eigenspectrum of the iteration matrix controlling convergence as long as the preconditioner relies on the incomplete factorization of the FE coefficient matrix. However, computational experience with mid‐large size problems shows that the above inexpensive operation can significantly accelerate the solver convergence, and to a minor extent also improve the final accuracy, as a result of a better solver stability to the accumulation and propagation of floating point round‐off errors. This is demonstrated with the aid of the least square logarithm (LSL) scaling algorithm on FE consolidation problems of increasing size up to more than 100 000. It is shown that a major source of numerical instability rests with the sub‐matrix which couples the structural to the fluid part of the underlying mathematical model. It is concluded that for mid‐large size, possibly difficult, FE consolidation problems left/right LSL scaling is to be always recommended when the incomplete factorization is used as a preconditioning technique. Copyright © 2003 John Wiley & Sons, Ltd. 相似文献
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D. N. Rachkovskii 《Astronomy Reports》2005,49(9):739-746
The theory required to calculate the phase matrix for resonance scattering in the presence of a magnetic field is set out. Interference effects between radiation from individual magnetic sublevels of the atom are taken into account. Errors in the algorithms used to calculate the phase matrix published earlier by other authors are identified. 相似文献
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In this work, we present an efficient matrix-free ensemble Kalman filter (EnKF) algorithm for the assimilation of large data
sets. The EnKF has increasingly become an essential tool for data assimilation of numerical models. It is an attractive assimilation
method because it can evolve the model covariance matrix for a non-linear model, through the use of an ensemble of model states,
and it is easy to implement for any numerical model. Nevertheless, the computational cost of the EnKF can increase significantly
for cases involving the assimilation of large data sets. As more data become available for assimilation, a potential bottleneck
in most EnKF algorithms involves the operation of the Kalman gain matrix. To reduce the complexity and cost of assimilating
large data sets, a matrix-free EnKF algorithm is proposed. The algorithm uses an efficient matrix-free linear solver, based
on the Sherman–Morrison formulas, to solve the implicit linear system within the Kalman gain matrix and compute the analysis.
Numerical experiments with a two-dimensional shallow water model on the sphere are presented, where results show the matrix-free
implementation outperforming an singular value decomposition-based implementation in computational time. 相似文献