Name
Abstract | ||
|---|---|---|
This paper presents computationally efficient implementations for Iterative Adaptive Approach (IAA) spectral estimation techniques for uniformly sampled data sets. By exploiting the methods inherent low displacement rank, together with the development of suitable Gohberg-Semencul representations, and the use of data dependent trigonometric polynomials, the proposed implementations are shown to offer a reduction of the necessary computational complexity with at least one order of magnitude. Numerical simulations together with theoretical complexity measures illustrate the achieved performance gain. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/ICASSP.2011.5947292 | ICASSP |
Keywords | Field | DocType |
signal representation,spectral estimation,fast algorithms,iterative adaptive approach,estimation,gohberg-semencul representations,spectral analysis,computational complexity,trigonometric polynomials,polynomials,iterative methods,covariance matrix,numerical simulation,signal processing,iteration method | Trigonometry,Mathematical optimization,Data set,Spectral density estimation,Polynomial,Iterative method,Computer science,Algorithm,Covariance matrix,Order of magnitude,Computational complexity theory | Conference |
ISSN | ISBN | Citations |
1520-6149 E-ISBN : 978-1-4577-0537-3 | 978-1-4577-0537-3 | 1 |
PageRank | References | Authors |
0.40 | 7 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| George-Othon Glentis | 1 | 88 | 13.19 |
| Andreas Jakobsson | 2 | 409 | 43.32 |