Back to Search
Start Over
Unsupervised Representation Learning of Structured Radio Communication Signals
- Publication Year :
- 2016
-
Abstract
- We explore unsupervised representation learning of radio communication signals in raw sampled time series representation. We demonstrate that we can learn modulation basis functions using convolutional autoencoders and visually recognize their relationship to the analytic bases used in digital communications. We also propose and evaluate quantitative met- rics for quality of encoding using domain relevant performance metrics.<br />Comment: 4 pages, 9 figures, currently under conference submission
- Subjects :
- Computer Science - Learning
Subjects
Details
- Database :
- arXiv
- Publication Type :
- Report
- Accession number :
- edsarx.1604.07078
- Document Type :
- Working Paper