Name
Title | ||
|---|---|---|
A new feature vector using local surrounding-line integral bispectra for identifying radio transmitters |
Abstract | ||
|---|---|---|
A novel method for identifying radio transmitters with the same model and manufacturing lot is proposed in this paper. The local surrounding-line integral bispectra are selected through the Fisherpsilas class-separability discriminant measure as the main feature parameters, and they are interfused with parameters significant for classification of the received signal to form a new identification feature vector. A radial basis function(RBF) neural network is implemented to realize classification and identification for the individual transmitter utilizing the new feature vector. The selected features are evaluated using sample data of ten FM stations with the same model and manufacturing lot. It is shown that they are highly discriminative even in low SNR. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ISSPA.2007.4555493 | ISSPA |
Keywords | Field | DocType |
identification feature vector,radial basis function networks,radio transmitters,surrounding line integral bispectra,radial basis function neural network,signal classification,radio transmitter identification,fisher class separability discriminant measure,artificial neural networks,frequency modulation,feature extraction,signal to noise ratio,feature vector,radial basis function | Transmitter,Line integral,Feature vector,Pattern recognition,Computer science,Signal-to-noise ratio,Feature extraction,Artificial intelligence,Frequency modulation,Artificial neural network,Discriminative model | Conference |
Volume | Issue | ISBN |
null | null | 978-1-4244-1779-8 |
Citations | PageRank | References |
0 | 0.34 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuhua Xu | 1 | 0 | 0.34 |
| Benxiong Huang | 2 | 168 | 19.36 |
| Zhengguang Xu | 3 | 84 | 8.83 |
| Yuchun Huang | 4 | 29 | 5.71 |