Name
Title | ||
|---|---|---|
Innovative Robust Modulation Classification Using Graph-Based Cyclic-Spectrum Analysis. |
Abstract | ||
|---|---|---|
A novel automatic modulation classification method based on the graph presentation of the cyclic spectrum is proposed. In our proposed scheme, the periodicity and the symmetry of the cyclic spectrum will be exploited to establish a concise feature representation of multiple graphs. The modulated signal is first transformed from the cycle-frequency domain into the graph domain. Consequently, the co... |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/LCOMM.2016.2618868 | IEEE Communications Letters |
Keywords | Field | DocType |
Feature extraction,Frequency modulation,Sparse matrices,Training,Indexes,Robustness | Adjacency matrix,Data mining,Monte Carlo method,Computer science,Algorithm,Feature extraction,Modulation,Real-time computing,Robustness (computer science),Hamming distance,Test data,Sparse matrix | Journal |
Volume | Issue | ISSN |
21 | 1 | 1089-7798 |
Citations | PageRank | References |
1 | 0.36 | 15 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xiao Yan | 1 | 7 | 4.88 |
| Guoyu Feng | 2 | 1 | 0.70 |
| Wu, Hsiao-Chun | 3 | 4 | 3.51 |
| Weidong Xiang | 4 | 394 | 37.44 |
| Qian Wang | 5 | 5 | 4.23 |