Phasma: An automatic modulation classification system based on Random Forest
| Autor: | Manolis Surligas, Kostis Triantafyllakis, Stefanos Papadakis, George Vardakis |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Quadrature modulation
Computer science business.industry Speech recognition Feature extraction Pattern recognition Minimum-shift keying Random forest Demodulation Artificial intelligence business Amplitude and phase-shift keying Quadrature amplitude modulation Computer Science::Information Theory Phase-shift keying |
| Zdroj: | DySPAN |
| DOI: | 10.1109/dyspan.2017.7920749 |
| Popis: | We propose an architecture that incorporates an automatic modulation classification (AMC) mechanism, assisted by Random Forest machine learning (ML) classifiers. Using this architecture we are able to distinguish a variety of digital and analog modulation schemes under various SNR environments. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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