This is a preview. Log in through your library . Abstract New estimates are provided for singular values of a matrix in this paper. These results generalize and improve corresponding estimates for ...
Abstract: Singular Value Decomposition (SVD) is often used in linear algebra and signal processing. SVD allows to decompose the original matrix into a product of three matrices, two of which are ...
Abstract: This paper proposes a fast-parallel method for singular value thresholding, aimed at low-rank analysis of many small matrices. In low-rank analysis, the problem of regularizing the nuclear ...
I will describe some properties of non-Hermitian random matrices and show their connections to non-Hermian Hamiltonians and open quantum systems in a large window of their parameter space. I will also ...
The singular value decomposition of a matrix is used to derive systematically the Moore-Penrose inverse for a matrix bordered by a row and a column, in addition to the Moore-Penrose inverse for the ...
I will describe some properties of non-Hermitian random matrices and show their connections to non-Hermian Hamiltonians and open quantum systems in a large window of their parameter space. I will also ...
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