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Adaptive Digital Twin Modeling with Control: Integration of Extended Kalman Filter-Based Recursive Sparse Nonlinear Identification with Model Predictive Control. [PDF]
Sensors (Basel)Wang J, Cao L, Cao Y, Gopaluni B.
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Topology constrained nonnegative matrix factorization for time varying omic expression. [PDF]
Sci RepDey A +3 more
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Local transcriptional covariation produces accurate estimates of cell phenotype. [PDF]
BioinformaticsOzbay S, Parekh A, Singh R.
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Computational methods for sparse matrices
Computer Physics Communications, 1980Abstract This paper is a survey of methods currently available for processing sparse matrices in a digital computer; specifically in the solution of linear algebraic equations and the eigenproblem.
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Generalizations of Davidson’s Method for Computing Eigenvalues of Sparse Symmetric Matrices
SIAM Journal on Scientific and Statistical Computing, 1986The method of \textit{E. R. Davidson} [J. Comput. Phys. 17, 87-94 (1975; Zbl 0293.65022)] for computing a few eigenpairs of large sparse symmetric matrices is analyzed as a method for using diagonal preconditioning (i.e. using an approximate inverse).
Morgan, Ronald B., Scott, David S.
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A hybrid method for the solution of sparse power system matrices on vector computers
38th Midwest Symposium on Circuits and Systems. Proceedings, 2002This paper describes a methodology for solving a linear system of equations on vector computer. The methodology combines direct and inverse factors. The decomposition and implementation of the direct solution in a CRAY Y-MPZE/232, and the performance results are discussed.
A. Padilha, A.R. Basso
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SIAM Journal on Scientific Computing, 2019
Summary: Obtaining high accuracy singular triplets for large sparse matrices is a significant challenge, especially when searching for the smallest triplets. Due to the difficulty and size of these problems, efficient methods must function iteratively, with preconditioners, and under strict memory constraints. In this research, we present a Golub-Kahan
Steven Goldenberg +2 more
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Summary: Obtaining high accuracy singular triplets for large sparse matrices is a significant challenge, especially when searching for the smallest triplets. Due to the difficulty and size of these problems, efficient methods must function iteratively, with preconditioners, and under strict memory constraints. In this research, we present a Golub-Kahan
Steven Goldenberg +2 more
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On the Method by Rostami for Computing the Real Stability Radius of Large and Sparse Matrices
SIAM Journal on Scientific Computing, 2016Summary: In a recent paper, \textit{M. W. Rostami} [SIAM J. Sci. Comput. 37, No. 5, S447--S471 (2015; Zbl 1325.65067)] has presented an interesting algorithm for the computation of the real pseudospectral abscissa and the real stability radius (aka the distance to instability) of a square matrix \(A \in \mathbb R^{n,n}\) in the spectral norm.
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