Brain-Inspired Learning for Intelligent Spectrum Sensing

Edge intelligence has been spoken about more than demonstrated, with a recent exception in voice and text processing. Designing for edge processing and intelligence faces expectations for real-time effective response and limitations in available space that lead to requirements for ultra-high-density hardware that operates on limited energy budgets and with high levels of security and reliability. A successful approach to such a design requires learning from nature how to trade off perception with action and survivability. This presentation will demonstrate an electronic equivalent of a biological architecture for designing a multi-sensory intelligent platform that includes an electromagnetic sensor for communications, a GPS, a navigation radar, and a camera.