Name
Title | ||
|---|---|---|
Analysing the performance of divide-and-conquer sequential matrix diagonalisation for large broadband sensor arrays |
Abstract | ||
|---|---|---|
A number of algorithms capable of iteratively calculating a polynomial matrix eigenvalue decomposition (PEVD) have been introduced. The PEVD is an extension of the ordinary EVD to polynomial matrices and will diagonalise a parahermitian matrix using paraunitary operations. Inspired by recent work towards a low complexity divide-and-conquer PEVD algorithm, this paper analyses the performance of this algorithm - named divide-and-conquer sequential matrix diagonalisation (DC-SMD) - for applications involving broadband sensor arrays of various dimensionalities. We demonstrate that by using the DC-SMD algorithm instead of a traditional alternative, PEVD complexity and execution time can be significantly reduced. This reduction is shown to be especially impactful for broadband multichannel problems involving large arrays. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/SiPS.2017.8109976 | 2017 IEEE International Workshop on Signal Processing Systems (SiPS) |
Keywords | Field | DocType |
low complexity divide-and-conquer PEVD algorithm,divide-and-conquer sequential matrix diagonalisation,paraunitary operations,PEVD,polynomial matrix eigenvalue decomposition,broadband multichannel problems,DC-SMD algorithm,broadband sensor arrays,parahermitian matrix,polynomial matrices | Signal processing,Approximation algorithm,Telecommunications,Polynomial,Polynomial matrix,Computer science,Matrix (mathematics),Parallel computing,Matrix decomposition,Algorithm,Eigendecomposition of a matrix,Divide and conquer algorithms | Conference |
ISBN | Citations | PageRank |
978-1-5386-0447-2 | 1 | 0.37 |
References | Authors | |
11 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Fraser K. Coutts | 1 | 8 | 4.31 |
| Keith Thompson | 2 | 7 | 3.31 |
| Weiss, Stephan | 3 | 209 | 33.25 |
| Ian K. Proudler | 4 | 63 | 12.78 |