Concatenating multi-antenna IQ signals into a CNN plus antenna-exchange augmentation improves modulation recognition accuracy and reduces complexity versus voting or averaging baselines in simulations.
Deep learning
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
fields
eess.SP 2verdicts
UNVERDICTED 2representative citing papers
Time-frequency transform plus per-slice gradient boosting detects EEG bursts in preterm infants with AUC 0.98, matching multi-feature baselines.
citing papers explorer
-
Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals
Concatenating multi-antenna IQ signals into a CNN plus antenna-exchange augmentation improves modulation recognition accuracy and reduces complexity versus voting or averaging baselines in simulations.
-
Machine learning without a feature set for detecting bursts in the EEG of preterm infants
Time-frequency transform plus per-slice gradient boosting detects EEG bursts in preterm infants with AUC 0.98, matching multi-feature baselines.