Name
Abstract | ||
|---|---|---|
In this paper we compare a variety of non-parametric time-frequency methods to determine the best timeñ frequency representation (TFR) for a collection of signals. These methods include quadratic time-frequency transforms, atomic decomposition and adaptive quadratic time-frequency transforms. The performance measures used to assess the TFRs include; twoñdimensional correlation, IF correlation and time-frequency resolution. Synthetic signals with differ- ent time-frequency characteristics were used in the compar- ison to show the strengths and weaknesses of the different time-frequency methods. It was determined that adaptive quadratic time-frequency representations provide the best overall performance and should be used if no a priori infor- mation about the time-frequency characteristics of a signal is known. |
Year | Venue | Keywords |
|---|---|---|
2005 | EUSIPCO | signal representation,signal resolution,time-frequency analysis,transforms,if correlation,tfr,adaptive quadratic time-frequency transforms,atomic decomposition,nonparametric time-frequency representations method,quadratic time-frequency transforms,time-frequency resolution,two-dimensional correlation |
Field | DocType | ISBN |
A priori and a posteriori,Quadratic equation,Algorithm,Theoretical computer science,Nonparametric statistics,Correlation,Time–frequency analysis,Strengths and weaknesses,Mathematics,Atomic decomposition,Atomic clock | Conference | 978-160-4238-21-1 |
Citations | PageRank | References |
3 | 0.42 | 1 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rankine, L. | 1 | 3 | 0.76 |
| Nathan Stevenson | 2 | 45 | 6.56 |
| Mostefa Mesbah | 3 | 184 | 27.26 |
| Boualem Boashash | 4 | 964 | 123.86 |