首页> 外文会议>International Conference of Computational Methods in Sciences and Engineering >Arrowheaded Enhanced Multivariance Products Representation for Matrices (AEMPRM): Specifically Focusing on Infinite Matrices and Converting Arrowheadedness to Tridiagonality
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Arrowheaded Enhanced Multivariance Products Representation for Matrices (AEMPRM): Specifically Focusing on Infinite Matrices and Converting Arrowheadedness to Tridiagonality

机译:矩阵增强的多功能产品表示矩阵(AEMPRM):特别关注无限矩阵并将箭头转换为Tridiacality

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In this work, Enhanced Multivariance Products Representation (EMPR) approach which is a Demiralp-and-his-group extension to the Sobol's High Dimensional Model Representation (HDMR) has been used as the basic tool. Their discrete form have also been developed and used in practice by Demiralp and his group in addition to some other authors for the decomposition of the arrays like vectors, matrices, or multiway arrays. This work specifically focuses on the decomposition of infinite matrices involving denumerable infinitely many rows and columns. To this end the target matrix is first decomposed to the sum of certain outer products and then each outer product is treated by Tridiagonal Matrix Enhanced Multivariance Products Representation (TMEMPR) which has been developed by Demiralp and his group. The result is a three-matrix-factor-product whose kernel (the middle factor) is an arrowheaded matrix while the pre and post factors are invertable matrices decomposed of the support vectors of TMEMPR. This new method is called as Arrowheaded Enhanced Multivariance Products Representation for Matrices. The general purpose is approximation of denumerably infinite matrices with the new method.
机译:在这项工作中,增强的多种度产品表示(EMPR)方法是Sobol的高维模型表示(HDMR)的Demiralp-and-His-Group扩展已被用作基本工具。除了用于分解阵列,矩阵或多道阵列的阵列的一些其他作者之外,Demiralp及其小组还通过Demiralp及其小组制定和使用了他们的离散形式。这项工作专注于无限矩阵的分解,涉及可贬值无限的行数和列。为此,目标矩阵首先分解到某些外产物的总和,然后通过Demiralp及其组开发的Tridiaconal矩阵增强多功能产品表示(TMEMPR)处理每个外产物。结果是一种三矩阵因子 - 产品,其内核(中间因子)是箭头波纹矩阵,而前后因子是由TMEMPR的支持向量分解的可逆性矩阵。这种新方法称为矩阵增强的矩阵多功能产品表示。通用是具有新方法的可恶劣无限矩阵的近似。

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