Reservoir Based Edge Training on RF Data To Deliver Intelligent and Efficient IoT Spectrum Sensors

Current radio frequency (RF) sensors at the Edge lack the computational resources to support practical, in-situ training for intelligent spectrum monitoring. This is true for sensor data classification in general. We propose a solution via Deep Delay Loop Reservoir Computing (DLR), a processing architecture that supports general machine learning algorithms on compact mobile devices by leveraging d...