Polynomial parahermitian matrices can accurately and elegantly capture the space-time covariance in broadband array problems. To factorise such matrices, a number of polynomial EVD (PEVD) algorithms have been suggested. At every step, these algorithms move various amounts of off-diagonal energy onto the diagonal, to eventually reach an approximate diagonalisation. In practical experiments, we have found that the relative performance of these algorithms depends quite significantly on the type of parahermitian matrix that is to be factorised. This paper aims to explore this performance space, and to provide some insight into the characteristics of PEVD algorithms
A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately usi...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue decomposition (EVD) ...
A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition...
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...
In broadband array processing applications, an extension of the eigenvalue decomposition (EVD) to pa...
Polynomial matrix eigenvalue decomposition (PEVD) algorithms have been shown to enable a solution to...
A variety of algorithms have been developed to compute an approximate polynomial matrix eigenvalue d...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
This paper extends the analysis of the recently introduced row-shift corrected truncation method for...
Recently a selection of sequential matrix diagonalisation (SMD) algorithms have been introduced whic...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
For parahermitian polynomial matrices, which can be used, for example, to characterise space-time co...
A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately usi...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue decomposition (EVD) ...
A number of algorithms for the iterative calculation of a polynomial matrix eigenvalue decomposition...
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...
In broadband array processing applications, an extension of the eigenvalue decomposition (EVD) to pa...
Polynomial matrix eigenvalue decomposition (PEVD) algorithms have been shown to enable a solution to...
A variety of algorithms have been developed to compute an approximate polynomial matrix eigenvalue d...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
This paper extends the analysis of the recently introduced row-shift corrected truncation method for...
Recently a selection of sequential matrix diagonalisation (SMD) algorithms have been introduced whic...
In this paper, we show that the paraunitary (PU) matrices that arise from the polynomial eigenvalue ...
For parahermitian polynomial matrices, which can be used, for example, to characterise space-time co...
A polynomial eigenvalue decomposition of paraher-mitian matrices can be calculated approximately usi...
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decompositi...
The polynomial matrix EVD (PEVD) is an extension of the conventional eigenvalue decomposition (EVD) ...