141 citations · 214 across the 13 of their papers we have counts for
7 papers · 2 filters
Semi-Supervised Radio Signal Identification
Timothy J. O'Shea, Nathan West, Matthew Vondal +1
Radio emitter recognition in dense multi-user environments is an important tool for optimizing spectrum utilization, identifying and minimizing interference, and enforcing spectrum…
Recurrent Neural Radio Anomaly Detection
Timothy J O'Shea, T. Charles Clancy, Robert W. McGwier
We introduce a powerful recurrent neural network based method for novelty detection to the application of detecting radio anomalies. This approach holds promise in significantly in…
End-to-End Radio Traffic Sequence Recognition with Deep Recurrent Neural Networks
Timothy J. O'Shea, Seth Hitefield, Johnathan Corgan
We investigate sequence machine learning techniques on raw radio signal time-series data. By applying deep recurrent neural networks we learn to discriminate between several applic…
Learning to Communicate: Channel Auto-encoders, Domain Specific Regularizers, and Attention
Timothy J O'Shea, Kiran Karra, T. Charles Clancy
We address the problem of learning efficient and adaptive ways to communicate binary information over an impaired channel. We treat the problem as reconstruction optimization throu…
Deep Reinforcement Learning Radio Control and Signal Detection with KeRLym, a Gym RL Agent
Timothy J. O'Shea, T. Charles Clancy
This paper presents research in progress investigating the viability and adaptation of reinforcement learning using deep neural network based function approximation for the task of…
Radio Transformer Networks: Attention Models for Learning to Synchronize in Wireless Systems
Timothy J O'Shea, Latha Pemula, Dhruv Batra +1
We introduce learned attention models into the radio machine learning domain for the task of modulation recognition by leveraging spatial transformer networks and introducing new r…