This toolbox contains a number of Matlab implementations of iterative algorithms to approximate the polynomial eigenvalue decomposition (EVD) of a parahermitian matrix. Parahermitian matrices arise e.g. when formulating covariance matrices for broadband array signals, and the term parahermitian hints as an extension of the (narrowband) Hermitian property to an generalised symmetry property of the polynomial matrix case.
The toolbox files are organised in four subdirectories:
To find out more about the PEVD, the contained algorithms, the toolbox license and related issues, please follow the links provided on the left.
We hope that you find this toolbox useful, and we look forward to any comments or feedback.
Stephan Weiss, Jamie Corr and Keith Thompson (University of Strathclyde, Glasgow, Scotland)
John G. McWhirter (Cardiff University, Wales)
Ian K. Proudler (Loughborough University, England)