Name
Abstract | ||
|---|---|---|
We present an algorithm that extracts analytic eigenvalues from a parahermitianmatrix. Operating in the discrete Fourier transform domain, an inner iteration re-establishes the lost association between bins via a maximum likelihood sequence detection driven by a smoothness criterion. An outer iteration continues until a desired accuracy for the approximation of the extracted eigenvalues has been achieved. The approach is compared to existing algorithms. |
Year | Venue | Field |
|---|---|---|
2019 | 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) | Applied mathematics,Mathematical optimization,Iterative approximation,Computer science,Matrix (mathematics),Maximum likelihood,Discrete Fourier transform,Smoothness,Eigenvalues and eigenvectors,Signal processing algorithms |
DocType | ISSN | Citations |
Conference | 1520-6149 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weiss, Stephan | 1 | 209 | 33.25 |
| Ian K. Proudler | 2 | 63 | 12.78 |
| Fraser K. Coutts | 3 | 8 | 4.31 |
| Jennifer Pestana | 4 | 37 | 9.93 |