Name
Abstract | ||
|---|---|---|
Recently a selection of sequential matrix diagonalisation (SMD) algorithms have been introduced which approximate polynomial eigenvalue decomposition of parahermitian matrices. These variants differ only in the search methods that are used to bring energy onto the zero-lag. Here we analyse the search methods in terms of their computational complexities for different sizes of parahermitian matrices which are verified through simulated execution times. Another important factor for these search methods is their ability to transfer energy. Simulations show that the more computationally complex search methods transfer a greater proportion of the off-diagonal energy onto the zero-lag over a selected range of parahermitian matrix sizes. Despite their higher cost per iteration experiments indicate that the more complex search algorithms still converge faster in real time. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/CAMSAP.2015.7383727 | 2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) |
Keywords | Field | DocType |
sequential matrix diagonalisation search strategies,SMD algorithms,approximate polynomial eigenvalue decomposition,paraHermitian matrices,search methods,computational complexities,energy transfer,off-diagonal energy,zero-lag,complex search algorithms | Approximation algorithm,Mathematical optimization,Search algorithm,Polynomial,Matrix (mathematics),Matrix decomposition,Eigendecomposition of a matrix,Hermitian matrix,Mathematics,Computational complexity theory | Conference |
Citations | PageRank | References |
0 | 0.34 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jamie Corr | 1 | 11 | 2.78 |
| Keith Thompson | 2 | 7 | 3.31 |
| Weiss, Stephan | 3 | 209 | 33.25 |
| John G. McWhirter | 4 | 214 | 28.77 |
| Ian K. Proudler | 5 | 63 | 12.78 |