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In-Sensor Radio Frequency Computing for Energy-Efficient Intelligent Radar
Radio Frequency Neural Networks (RFNNs) have demonstrated advantages in realizing intelligent applications across various domains.
Temporal credit assignment for one-shot learning utilizing a phase transition material
Design of hardware based on biological principles of neuronal computation and plasticity in the brain is a leading approach to realizing energy- and sample-efficient artificial intelligence and learning machines.
Programming Wireless Security through Learning-Aided Spatiotemporal Digital Coding Metamaterial Antenna
Physical layer (PHY) security has been put forth as a cost-effective alternative to cryptographic mechanisms that can circumvent the need for explicit key exchange between communication devices, owing to the fact that PHY security relies on the physics of the signal transmission for providing security.
Simultaneous Monitoring of Multiple People's Vital Sign Leveraging a Single Phased-MIMO Radar
Based on the designed TDM phased-MIMO radar, we develop a system to automatically localize multiple human subjects and estimate their vital signs.
Modeling the Impact of 5G Leakage on Weather Prediction
The 5G band allocated in the 26 GHz spectrum referred to as 3GPP band n258, has generated a lot of anxiety and concern in the meteorological data forecasting community including the National Oceanic and Atmospheric Administration (NOAA).
