Showing eess.SPShow all
3 papers · 1 filter
eess.SP2025
Deep-Learning-Based Classification of Digitally Modulated Signals
John A. Snoap
This dissertation presents several novel deep-learning (DL)-based approaches for classifying digitally modulated signals, one method of which involves the use of capsule networks (…
eess.SP2023
Novel Nonlinear Neural-Network Layers for High Performance and Generalization in Modulation-Recognition Applications
John A. Snoap, Dimitrie C. Popescu, Chad M. Spooner
The paper presents a novel type of capsule network (CAP) that uses custom-defined neural network (NN) layers for blind classification of digitally modulated signals using their in-…
eess.SP2023
On Deep Learning Classification of Digitally Modulated Signals Using Raw I/Q Data
John A. Snoap, Dimitrie C. Popescu, Chad M. Spooner
The paper considers the problem of deep-learning-based classification of digitally modulated signals using I/Q data and studies the generalization ability of a trained neural netwo…