Konrád Kajdi

Convolutional and Variational Autoencoders with Supervised Classifiers for RF Spectrum Anomaly Detection

The results indicate that hybrid encoder–classifier approaches can provide an effective practical solution for anomaly detection in spectrum monitoring environments, and are limited to the investigated FM-band dataset and require further validation across broader spectrum environments.