Name
Title | ||
|---|---|---|
Investigation Of A Polynomial Matrix Generalised Evd For Multi-Channel Wiener Filtering |
Abstract | ||
|---|---|---|
State-of-the-art narrowband noise cancellation techniques utilise the generalised eigenvalue decomposition (GEVD) for multi-channel Wiener filtering, which can be applied to independent frequency bins in order to achieve broadband processing. Here we investigate the extension of the GEVD to broadband, polynomial matrices, akin to strategies that have already been developed by McWhirter et. al on the polynomial matrix eigenvalue decomposition (PEVD). In our approach we extend the Cholesky method for calculating the scalar GEVD to polynomial matrices. In this paper we outline our Cholesky-like approach, which utilises recently developed techniques for polynomial matrix spectral factorisation and polynomial matrix inversion. |
Year | Venue | Field |
|---|---|---|
2016 | 2016 50TH ASILOMAR CONFERENCE ON SIGNALS, SYSTEMS AND COMPUTERS | Wiener filter,Mathematical optimization,Polynomial matrix,Polynomial,Matrix (mathematics),Computer science,Matrix decomposition,Electronic engineering,Eigendecomposition of a matrix,Matrix polynomial,Cholesky decomposition |
DocType | ISSN | Citations |
Conference | 1058-6393 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jamie Corr | 1 | 11 | 2.78 |
| Jennifer Pestana | 2 | 37 | 9.93 |
| Weiss, Stephan | 3 | 209 | 33.25 |
| Ian K. Proudler | 4 | 63 | 12.78 |
| Soydan Redif | 5 | 169 | 17.30 |
| Marc Moonen | 6 | 3673 | 326.91 |