Name
Abstract | ||
|---|---|---|
The detection and characterization of burst signals are challenging tasks for time-frequency analysis, due to their very short duration. This paper investigates in this context the recurrence plot analysis (RPA) method, from which it derives the vector samples processing (VeSP) concept. The paper shows that VeSP is a generic framework that unifies signal processing concepts like histogram and autocorrelation, which it also generalizes and extends. Results of VeSP based tools are provided, concerning detection of transient signals, noise reduction, and frequency estimation. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ISSPA.2012.6310462 | ISSPA |
Keywords | Field | DocType |
noise reduction,vectors,time frequency analysis,signal detection,signal to noise ratio | Noise reduction,Signal processing,Histogram,Pattern recognition,Detection theory,Computer science,Speech recognition,Artificial intelligence,Time–frequency analysis,Recurrence plot,Autocorrelation | Conference |
ISBN | Citations | PageRank |
978-1-4673-0380-4 | 1 | 0.43 |
References | Authors | |
2 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Florin-Marian Birleanu | 1 | 2 | 0.96 |
| Ion Candel | 2 | 1 | 1.11 |
| Cornel Ioana | 3 | 117 | 26.55 |
| Cedric Gervaise | 4 | 3 | 2.64 |
| Alexandru Serbanescu | 5 | 7 | 2.54 |
| Gheorghe Şerban | 6 | 1 | 1.45 |