Many applications give rise to nonlinear eigenvalue problems with an underlying structured matrix polynomial. In this paper several useful classes of structured polynomial (e.g., palindromic, even, odd) are identified and the relationships between them explored. A special class of linearizations that reflect the structure of these polynomials, and therefore preserve symmetries in their spectra, is introduced and investigated. We analyze the existence and uniqueness of such linearizations, and show how they may be systematically constructed
AbstractWe discuss the eigenvalue problem for general and structured matrix polynomials which may be...
AbstractThe standard way to solve polynomial eigenvalue problems P(λ)x=0 is to convert the matrix po...
The standard way to solve polynomial eigenvalue problems P (λ)x = 0 is to convert the matrix polynom...
Many applications give rise to nonlinear eigenvalue problems with an underlying structured matrix po...
Abstract. Many applications give rise to nonlinear eigenvalue problems with an underlying structured...
Abstract. Many applications give rise to nonlinear eigenvalue problems with an underlying structured...
Abstract. Many applications give rise to nonlinear eigenvalue problems with an underlying structured...
Abstract. Palindromic polynomial eigenvalue problems and related classes of structured eigenvalue pr...
Palindromic polynomial eigenvalue problems and related classes of structured eigenvalue problems are...
The classical approach to investigating polynomial eigenvalue problems is linearization, where the u...
The classical approach to investigating polynomial eigenvalue problems is linearization, where the u...
AbstractThis work is concerned with eigenvalue problems for structured matrix polynomials, including...
The standard way to solve polynomial eigenvalue problems $P(\la)x=0$ is to convert the matrix polyno...
Matrix polynomial eigenproblems arise in many application areas, both directly and as approximations...
The standard way to solve polynomial eigenvalue problems $P(\la)x=0$ is to convert the matrix polyno...
AbstractWe discuss the eigenvalue problem for general and structured matrix polynomials which may be...
AbstractThe standard way to solve polynomial eigenvalue problems P(λ)x=0 is to convert the matrix po...
The standard way to solve polynomial eigenvalue problems P (λ)x = 0 is to convert the matrix polynom...
Many applications give rise to nonlinear eigenvalue problems with an underlying structured matrix po...
Abstract. Many applications give rise to nonlinear eigenvalue problems with an underlying structured...
Abstract. Many applications give rise to nonlinear eigenvalue problems with an underlying structured...
Abstract. Many applications give rise to nonlinear eigenvalue problems with an underlying structured...
Abstract. Palindromic polynomial eigenvalue problems and related classes of structured eigenvalue pr...
Palindromic polynomial eigenvalue problems and related classes of structured eigenvalue problems are...
The classical approach to investigating polynomial eigenvalue problems is linearization, where the u...
The classical approach to investigating polynomial eigenvalue problems is linearization, where the u...
AbstractThis work is concerned with eigenvalue problems for structured matrix polynomials, including...
The standard way to solve polynomial eigenvalue problems $P(\la)x=0$ is to convert the matrix polyno...
Matrix polynomial eigenproblems arise in many application areas, both directly and as approximations...
The standard way to solve polynomial eigenvalue problems $P(\la)x=0$ is to convert the matrix polyno...
AbstractWe discuss the eigenvalue problem for general and structured matrix polynomials which may be...
AbstractThe standard way to solve polynomial eigenvalue problems P(λ)x=0 is to convert the matrix po...
The standard way to solve polynomial eigenvalue problems P (λ)x = 0 is to convert the matrix polynom...