Results 71 to 80 of about 62,500 (93)
Effective use of latent semantic indexing and computational linguistics in biological and biomedical applications. [PDF]
Chen H, Martin B, Daimon CM, Maudsley S.
europepmc +1 more source
Approximate low-rank factorization with structured factors
An approximate rank revealing factorization problem with structure constraints on the normalized factors is considered. Examples of structure, motivated by an application in microarray data analysis, are sparsity, nonnegativity, periodicity, and ...
Niranjan, Mahesan, Markovsky, Ivan
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On frequency-weighted coprime factorization based controller reduction [PDF]
We consider the efficient solution of a class of coprime factorization based controller approximation problems by using frequency-weighted balancing related model reduction approaches.
Varga, Andras
core
Thiran Filters for Wideband DSP-Based Multi-Beam True Time Delay RF Sensing Applications. [PDF]
Perera SM, Rathnasekara G, Madanayake A.
europepmc +1 more source
A Sparse Hierarchical <i>hp</i>-Finite Element Method on Disks and Annuli. [PDF]
Papadopoulos IPA, Olver S.
europepmc +1 more source
A Superintegrable Quantum Field Theory. [PDF]
De Clerck M, Evnin O.
europepmc +1 more source
Modifying a Sparse Cholesky Factorization
Given a sparse symmetric positive de nite matrix AA and an associated sparse Cholesky factorization LDL , we develop sparse techniques for obtaining the new factorization associated with either adding a column to A or deleting a column from A ...
Cholesky Factorization Ldl +3 more
core
This chapter introduces and methodically develops the important and useful topic of bidiagonal factorization. Factorization of matrices is one of the most important topics in matrix theory, and plays a central role in many related applied areas such as numerical analysis and statistics. Investigating when a class of matrices admits a particular type of
Shaun M. Fallat, Charles R. Johnson
exaly +3 more sources
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Successively Ordered Elementary Bidiagonal Factorization
SIAM Journal on Matrix Analysis and Applications, 2001Let \(I\) be the identity matrix and \(E_{ij}\) the matrix with \((i,j)\)-entry \(1\) and zeros in all other positions. Define \(L_i(s)=I+sE_{i,i-1}\) and \(U_j(t)=I+tE_{j-1,j},\) where \(s,t\) are elements in a given field \(F.\) The matrices \(L_i(s)\) and \(U_j(t)\) are called elementary bidiagonal matrices. The authors give necessary and sufficient
D D Olesky
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