Search Results for author:
Found 2 papers, 1 papers with code
A Novel Approach to WaveNet Architecture for RF Signal Separation with Learnable Dilation and Data Augmentation
In this paper, we address the intricate issue of RF signal separation by presenting a novel adaptation of the WaveNet architecture that introduces learnable dilation parameters, significantly enhancing signal separation in dense RF spectrums.
Defeating Proactive Jammers Using Deep Reinforcement Learning for Resource-Constrained IoT Networks
However, their robustness against the growing complexity of internet-of-thing (IoT) networks and diverse jamming attacks is still limited.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
