Results 301 to 310 of about 454,491 (346)
Minimising the impact of stable <sup>208</sup>Pb on recovery of <sup>212</sup>Pb from a generator. [PDF]
Roberts R +7 more
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Kinetically Consistent Coarse Graining Using Kernel-Based Extended Dynamic Mode Decomposition. [PDF]
Nateghi V, Nüske F.
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A cyclic redundancy check aided encoding construction method for list sphere polar decoder. [PDF]
Hu W +6 more
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Proceedings of the 5th international conference on Computer systems and technologies - CompSysTech '04, 2004
The paper considers a new approach for regression based construction of transition matrix using market spread curves or historic probabilities of default. The generated transition matrix could be adjusted according to the credit year quality and the systematic component or using an aggregation schema.
Anatoliy Antonov, Yanka Yanakieva
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The paper considers a new approach for regression based construction of transition matrix using market spread curves or historic probabilities of default. The generated transition matrix could be adjusted according to the credit year quality and the systematic component or using an aggregation schema.
Anatoliy Antonov, Yanka Yanakieva
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The generalized path matrix and energy
Discrete Mathematics, Algorithms and Applications, 2022We define the path Laplacian matrix and the path signless Laplacian matrix of a simple connected graph G as [Formula: see text] and [Formula: see text], respectively, where [Formula: see text] is the path matrix and [Formula: see text] is the diagonal matrix of the vertex transmissions. The generalized path matrix is [Formula: see text], for [Formula:
Pengli Lu, Rui Luan
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A Generalization of the Frank Matrix
SIAM Journal on Scientific and Statistical Computing, 1986A class of test matrices for eigenvalue routines is given, which includes the Frank matrix [cf. \textit{W. L. Frank} [J. Soc. Ind. Appl. Math. 6, 378- 392 (1958; Zbl 0198.208)]. It is shown that the eigensystem can be calculated accurately. An explanation for the poor condition of the test matrices is given.
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Generalized Polytopic Matrix Factorization
ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021Polytopic Matrix Factorization (PMF) is introduced as a flexible data decomposition tool with potential applications in unsupervised learning. PMF assumes a generative model where observations are lossless linear mixtures of some samples drawn from a particular polytope.
Gokcan Tatli, Alper T. Erdogan
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On the inverse of a general pentadiagonal matrix
Applied Mathematics and Computation, 2008In this paper, employing the general Doolittle factorization, an efficient algorithm is developed to find the inverse of a general pentadiagonal matrix which is suitable for implementation using computer algebra systems software such as Matlab and Maple. Examples are given to illustrate the efficiency of the algorithm.
Xi-Le Zhao, Ting-Zhu Huang
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A Generalization of a Matrix Occupancy Problem
Biometrics, 1976An extension of the so-called committee problem is discussed in terms of the occupancy of a certain matrix whose row totals are taken as fixed, and whose cell entries are constrained to lie between zero and defined maxima. A statistic is constructed as a function of the column totals and used to test the significance of a column effect, irrespective of
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