In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue decomposition (PEVD) of a parahermitian matrix are not unique. In particular, arbitrary shifts (delays) of polynomials in one row of a PU matrix yield another PU matrix that admits the same PEVD. To keep the order of such a PU matrix as low as possible, we pro- pose a row-shift correction. Using the example of an iterative PEVD algorithm with previously proposed truncation of the PU matrix, we demonstrate that a considerable shortening of the PU order can be accomplished when using row-corrected truncation
In recent years, several algorithms for the iterative calculation of a polynomial matrix eigenvalue ...
This paper introduces a causality constrained sequential matrix diagonalisation (SMD) algorithm, wh...
In this paper, we propose an algorithm for computing an approximate polynomial matrix eigenvalue dec...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
This paper extends the analysis of the recently introduced row-shift corrected truncation method for...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
Polynomial parahermitian matrices can accurately and elegantly capture the space-time covariance in ...
In this work we present a new method of controlling the order growth of polynomial matrices in the m...
A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately usi...
For parahermitian polynomial matrices, which can be used, for example, to characterise space-time co...
A number of algorithms are capable of iteratively calculating a polynomial matrix eigenvalue decompo...
A recent class of sequential matrix diagonalisation (SMD) algorithms have been demonstrated to provi...
A variety of algorithms have been developed to compute an approximate polynomial matrix eigenvalue d...
In recent years, several algorithms for the iterative calculation of a polynomial matrix eigenvalue ...
This paper introduces a causality constrained sequential matrix diagonalisation (SMD) algorithm, wh...
In this paper, we propose an algorithm for computing an approximate polynomial matrix eigenvalue dec...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
This paper extends the analysis of the recently introduced row-shift corrected truncation method for...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
Polynomial parahermitian matrices can accurately and elegantly capture the space-time covariance in ...
In this work we present a new method of controlling the order growth of polynomial matrices in the m...
A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately usi...
For parahermitian polynomial matrices, which can be used, for example, to characterise space-time co...
A number of algorithms are capable of iteratively calculating a polynomial matrix eigenvalue decompo...
A recent class of sequential matrix diagonalisation (SMD) algorithms have been demonstrated to provi...
A variety of algorithms have been developed to compute an approximate polynomial matrix eigenvalue d...
In recent years, several algorithms for the iterative calculation of a polynomial matrix eigenvalue ...
This paper introduces a causality constrained sequential matrix diagonalisation (SMD) algorithm, wh...
In this paper, we propose an algorithm for computing an approximate polynomial matrix eigenvalue dec...