Now showing items 1-4 of 4
Classifying bent radio galaxies from a mixture of point-like/extended images with machine learning
The hypothesis that bent radio sources are supposed to be found in rich, massive galaxy clusters and the avalibility of huge amount of data from radio surveys have fueled our motivation to use Machine Learning (ML) to ...
Radio frequency interference detection using machine learning
Radio frequency interference (RFI) has plagued radio astronomy which potentially might be as bad or worse by the time the Square Kilometre Array (SKA) comes up. RFI can be either internal (generated by instruments) or ...
The performance of feature-based classification of digital modulations under varying SNR and fading channel conditions
Feature-based classification is a method used for automatic modulation classification of communication signals. This method requires extraction of various features from a signal. One of the approaches for feature extraction ...
Machine learning for radio frequency interference mitigation using polarization
Radio frequency interference (RFI) is electromagnetic interference (EMI) from signals in the radio frequencies of the electromagnetic spectrum. RFI reduces the sensitivity of radio telescope and produces artefacts in ...