Matrix polynomials and moment problems are significant areas of study in mathematics, particularly in the fields of control theory, numerical analysis, and probability. Matrix polynomials are ...

Abstract: In this paper, we propose an algorithm for computing an approximate polynomial matrix eigenvalue decomposition (PEVD). The PEVD of a para-Hermitian matrix yields a factorisation into a ...

In my work, I get some polynomials of the form (e.g., the paper) $$F(t, t_1, ..., t_M) = \sum_k C_k t_0^{n_{0,k}} t_1^{n_{1,k}} ... t_M^{n_{M,k}} \exp \left( \sum_{l ...

This codebase was developed solely for academic benchmarking purposes related to the above paper. It is not production-grade, and the code is not organized or maintained beyond what was necessary to ...

In this paper, the notion of equitable partitions (EP) is used to study the eigenvalues of Euclidean distance matrices (EDMs). In particular, EP is used to obtain the characteristic polynomials of ...

Mark Jerrum, Alistair Sinclair (UC Berkeley) and Eric Vigoda (Georgia Tech) received the Association for Computing Machinery (ACM) Test of Time Award at a virtual ceremony on Wednesday 23 June at the ...

In this video we will learn about integral power of a matrix, matrix polynomial, symmetric matrix and skew-symmetric matrix. Your career begins here! At Jagranjosh ...

ABSTRACT: In this paper we introduce Humbert matrix polynomials of two variables. Some hypergeometric matrix representations of the Humbert matrix polynomials of two variables, the double generating ...

ABSTRACT: The object of this paper is to present a new generalization of the Hermite matrix polynomials by means of the hypergeometric matrix function. An integral representation, differential ...

Your career begins here! At Jagranjosh.com, our vision is to enable the youth to make informed life decisions, and our mission is to create credible and actionable ...