141 citations · 290 across the 58 of their papers we have counts for
4 papers · 2 filters
The RFML Ecosystem: A Look at the Unique Challenges of Applying Deep Learning to Radio Frequency Applications
Lauren J. Wong, William H. Clark, Bryse Flowers +3
While deep machine learning technologies are now pervasive in state-of-the-art image recognition and natural language processing applications, only in recent years have these techn…
Predicting Bit Error Rate from Meta Information using Random Forests
Jianyuan Yu, Yue Xu, Hussein Metwaly Saad +1
With the increasing power of machine learning-based reasoning, the use of meta-information (e.g., digital signal modulation parameters, channel conditions, etc.) to predict the per…
Deep Reinforcement Learning Control for Radar Detection and Tracking in Congested Spectral Environments
Charles E. Thornton, Mark A. Kozy, R. Michael Buehrer +2
In this paper, dynamic non-cooperative coexistence between a cognitive pulsed radar and a nearby communications system is addressed by applying nonlinear value function approximati…
Interference Classification Using Deep Neural Networks
Jianyuan Yu, Mohammad Alhassoun, R. Michael Buehrer
The recent success in implementing supervised learning to classify modulation types suggests that other problems akin to modulation classification would eventually benefit from tha…