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We devise a method that reduces the problem of classifying systems of forms and linear mappings to the problem of classifying systems of linear mappings. Canonical matrices of (i) bilinear or sesquilinear forms, (ii) pairs of symmetric,…

Representation Theory · Mathematics 2008-01-08 Vladimir V. Sergeichuk

We derive approximation algorithms for the nonnegative matrix factorization problem, i.e. the problem of factorizing a matrix as the product of two matrices with nonnegative coefficients. We form convex approximations of this problem which…

Optimization and Control · Mathematics 2012-07-03 Vijay Krishnamurthy , Alexandre d'Aspremont

While existing algorithms may be used to solve a linear system over a general field in matrix-multiplication time, the complexity of constructing a symmetric triangular factorization (LDL) has received relatively little formal study. The…

Numerical Analysis · Mathematics 2025-06-26 Edgar Solomonik

Hierarchical matrices approximate a given matrix by a decomposition into low-rank submatrices that can be handled efficiently in factorized form. $\mathcal{H}^2$-matrices refine this representation following the ideas of fast multipole…

Numerical Analysis · Mathematics 2024-04-24 Steffen Börm

Given a structured matrix $A$ we study the problem of finding the closest normal matrix with the same structure. The structures of our interest are: Hamiltonian, skew-Hamiltonian, per-Hermitian, and perskew-Hermitian. We develop a…

Numerical Analysis · Mathematics 2024-03-20 Erna Begovic

This work provides explicit characterizations and formulae for the minimal polynomials of a wide variety of structured $4\times 4$ matrices. These include symmetric, Hamiltonian and orthogonal matrices. Applications such as the complete…

Mathematical Physics · Physics 2010-10-12 Viswanath Ramakrishna , Yassmin Ansari , Fred Costa

Symmetric nonnegative matrix factorization (NMF), a special but important class of the general NMF, is demonstrated to be useful for data analysis and in particular for various clustering tasks. Unfortunately, designing fast algorithms for…

Machine Learning · Computer Science 2018-11-15 Zhihui Zhu , Xiao Li , Kai Liu , Qiuwei Li

We introduce and develop a theory of orthogonality with respect to Sobolev inner products on the real line for sequences of functions with a tridiagonal, skew-Hermitian differentiation matrix. While a theory of such L2-orthogonal systems is…

Classical Analysis and ODEs · Mathematics 2022-06-16 Arieh Iserles , Marcus Webb

In this paper, we introduce novel fast matrix inversion algorithms that leverage triangular decomposition and recurrent formalism, incorporating Strassen's fast matrix multiplication. Our research places particular emphasis on triangular…

Numerical Analysis · Mathematics 2026-02-05 Mohamed Kamel Riahi

In this paper we derive and analyze an algorithm for inverting quaternion matrices. The algorithm is an analogue of the Frobenius algorithm for the complex matrix inversion. On the theory side, we prove that our algorithm is more efficient…

Numerical Analysis · Mathematics 2023-05-05 Qiyuan Chen , J. Uhlmann , Ke Ye

We consider the design of an orthogonal symmetric/antisymmetric multiwavelet from its matrix product filter by matrix spectral factorization (MSF). As a test problem, we construct a simple matrix product filter with desirable properties,…

Computer Vision and Pattern Recognition · Computer Science 2021-08-20 Vasil Kolev , Todor Cooklev , Fritz Keinert

Tridiagonal canonical forms of square matrices under congruence or *congruence, pairs of symmetric or skew-symmetric matrices under congruence, and pairs of Hermitian matrices under *congruence are given over an algebraically closed field…

Representation Theory · Mathematics 2008-01-14 Vyacheslav Futorny , Roger A. Horn , Vladimir V. Sergeichuk

A unified theory of orthogonal polynomials of a discrete variable is presented through the eigenvalue problem of hermitian matrices of finite or infinite dimensions. It can be considered as a matrix version of exactly solvable Schr\"odinger…

Classical Analysis and ODEs · Mathematics 2008-11-26 Satoru Odake , Ryu Sasaki

If a tensor with various symmetries is properly unfolded, then the resulting matrix inherits those symmetries. As tensor computations become increasingly important it is imperative that we develop efficient structure preserving methods for…

Numerical Analysis · Computer Science 2014-12-01 Charles Van Loan , Joseph Vokt

The multiplication of matrices is an important arithmetic operation in computational mathematics. In the context of hierarchical matrices, this operation can be realized by the multiplication of structured block-wise low-rank matrices,…

Numerical Analysis · Mathematics 2018-05-24 Jürgen Dölz , Helmut Harbrecht , Michael D. Multerer

A matrix-compression algorithm is derived from a novel isogenic block decomposition for square matrices. The resulting compression and inflation operations possess strong functorial and spectral-permanence properties. The basic observation…

Rings and Algebras · Mathematics 2022-11-01 Alexander Belton , Dominique Guillot , Apoorva Khare , Mihai Putinar

Three ways of constructing a non-Hermitian matrix with possible all real eigenvalues are discussed. They are PT symmetry, pseudo-Hermiticity, and generalized PT symmetry. Parameter counting is provided for each class. All three classes of…

Quantum Physics · Physics 2012-12-11 Jia-wen Deng , Uwe Guenther , Qing-hai Wang

We analyze two algorithms for computing the symplectic $LL^T$ factorization $A=LL^T$ of a given symmetric positive definite symplectic matrix $A$. The first algorithm $W_1$ is an implementation of the $HH^T$ factorization from [Dopico et…

Numerical Analysis · Mathematics 2022-04-11 Maksymilian Bujok , Alicja Smoktunowicz , Grzegorz Borowik

We present a non-commutative algorithm for the multiplication of a 2 x 2 block-matrix by its adjoint, defined by a matrix ring anti-homomorphism. This algorithm uses 5 block products (3 recursive calls and 2 general products)over C or in…

Symbolic Computation · Computer Science 2021-01-05 Jean-Guillaume Dumas , Clément Pernet , Alexandre Sedoglavic

Randomized sampling has recently been demonstrated to be an efficient technique for computing approximate low-rank factorizations of matrices for which fast methods for computing matrix vector products are available. This paper describes an…

Numerical Analysis · Mathematics 2008-06-17 Per-Gunnar Martinsson