24 citations · 68 across the 19 of their papers we have counts for
4 papers · 1 filter
Reservoir Based Edge Training on RF Data To Deliver Intelligent and Efficient IoT Spectrum Sensors
Silvija Kokalj-Filipovic, Paul Toliver, William Johnson +1
Current radio frequency (RF) sensors at the Edge lack the computational resources to support practical, in-situ training for intelligent spectrum monitoring, and sensor data classi…
Practical Fingerprinting of RF Devices in the Wild
Silvija Kokalj-Filipovic, Luke Boegner, Robert D. Miller
We present a new RF fingerprinting technique for wireless emitters that is based on a simple, easily and efficiently retrainable Ridge Regression (RR) classifier. The RR learns to…
Deep Delay Loop Reservoir Computing for Specific Emitter Identification
Silvija Kokalj-Filipovic, Paul Toliver, William Johnson +2
Current AI systems at the tactical edge lack the computational resources to support in-situ training and inference for situational awareness, and it is not always practical to leve…
Mitigation of Adversarial Examples in RF Deep Classifiers Utilizing AutoEncoder Pre-training
Silvija Kokalj-Filipovic, Rob Miller, Nicholas Chang +1
Adversarial examples in machine learning for images are widely publicized and explored. Illustrations of misclassifications caused by slightly perturbed inputs are abundant and com…