Name
Title | ||
|---|---|---|
Specific emitter identification based on Hilbert-Huang transform-based time-frequency-energy distribution features. |
Abstract | ||
|---|---|---|
A novel specific emitter identification method based on transient communication signal's time-frequency-energy distribution obtained by Hilbert-Huang transform (HHT) is proposed. The transient starting point is detected using the phase-based method and the transient endpoint is detected using a self-adaptive threshold based on the HHT-based energy trajectory. Thirteen features that represent both ... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1049/iet-com.2013.0865 | IET Communications |
Keywords | Field | DocType |
Hilbert transforms,mobile computing,mobile handsets,principal component analysis,signal detection,support vector machines,telecommunication security | Detection theory,Common emitter,Real-time computing,Artificial intelligence,Feature vector,Pattern recognition,Support vector machine,Radio frequency,Fingerprint,Speech recognition,Time–frequency analysis,Mathematics,Hilbert–Huang transform | Journal |
Volume | Issue | ISSN |
8 | 13 | 1751-8628 |
Citations | PageRank | References |
10 | 0.77 | 12 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yingjun Yuan | 1 | 10 | 0.77 |
| Zhi-Tao Huang | 2 | 215 | 23.11 |
| Hao Wu | 3 | 10 | 1.11 |
| Xiang Wang | 4 | 45 | 11.30 |