منابع مشابه
Updating the partial singular value decomposition in latent semantic indexing
Latent semantic indexing (LSI) is a method of information retrieval that relies heavily on the partial singular value decomposition (PSVD) of the term-document matrix representation of a dataset. Calculating the PSVD of large term-document matrices is computationally expensive; hence in the case where terms or documents are merely added to an existing dataset, it is extremely beneficial to upda...
متن کاملپیشنهاد روش جدیدی برای محاسبه polynomial singular value decomposition ) psvd )
در این پایان نامه به معرفی روشهای مختلف محاسبه psvd می پردازیم. بخشی از این روشها به بررسی روشهای مختلف محاسبه psvd در مقالات مطالعه شده می پردازد که می توان به محاسبهpsvd با استفاده از الگوریتمهای pqrd و pevd و sbr2 و محاسبه psvd براساس تکنیک kogbetliantz و روش پارامتریک برای محاسبه psvd اشاره نمود. بخش بعدی نیز به بررسی روشهای مستقیم پیشنهادی محاسبه psvd برای ماتریسهای 2×2و2× n و n×2 و 3× n و...
15 صفحه اولUpdating Singular Value Decomposition for Rank One Matrix Perturbation
An efficient Singular Value Decomposition (SVD) algorithm is an important tool for distributed and streaming computation in big data problems. It is observed that update of singular vectors of a rank-1 perturbed matrix is similar to a Cauchy matrix-vector product. With this observation, in this paper, we present an efficient method for updating Singular Value Decomposition of rank1 perturbed ma...
متن کاملThe Singular Value Decomposition
Carlo Tomasi Any m n matrix of rank r transforms the unit sphere in Rn into an r-dimensional hyperellipsoid in Rm. For instance, the rank-2 matrix A = 1 p2 264 p3 p3 3 3 1 1 375 (1) transforms the unit circle on the plane into an ellipse embedded in three-dimensional space. Figure 1 shows the map y = Ax : Two diametrically opposite points on the unit circle are mapped into the two endpoints of ...
متن کاملSingular Value Decomposition (SVD) and Generalized Singular Value Decomposition (GSVD)
The singular value decomposition (SVD) is a generalization of the eigen-decomposition which can be used to analyze rectangular matrices (the eigen-decomposition is definedonly for squaredmatrices). By analogy with the eigen-decomposition, which decomposes a matrix into two simple matrices, the main idea of the SVD is to decompose a rectangular matrix into three simple matrices: Two orthogonal m...
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ژورنال
عنوان ژورنال: Journal of Computational and Applied Mathematics
سال: 2004
ISSN: 0377-0427
DOI: 10.1016/j.cam.2003.12.039