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Found 8 papers, 1 papers with code
Theoretical Analysis of Heterodyne Rydberg Atomic Receiver Sensitivity Based on Transit Relaxation Effect and Frequency Detuning
We conduct a theoretical investigation into the impacts of local microwave electric field frequency detuning, laser frequency detuning, and transit relaxation rate on enhancing heterodyne Rydberg atomic receiver sensitivity.
DACFL: Dynamic Average Consensus Based Federated Learning in Decentralized Topology
Federated learning (FL) is a burgeoning distributed machine learning framework where a central parameter server (PS) coordinates many local users to train a globally consistent model.
Resonant Beam Communications with Echo Interference Elimination
Resonant beam communications (RBCom) is capable of providing wide bandwidth when using light as the carrier.
Knowledge-Driven Machine Learning: Concept, Model and Case Study on Channel Estimation
The power of big data and machine learning has been drastically demonstrated in many fields during the past twenty years which somehow leads to the vague even false understanding that the huge amount of precious human knowledge accumulated to date no longer seems to matter.
Quantumized Microwave Detection Based on $Λ$-Type Three-level Superconducting System: HMM Modeling and Performance Prediction
Based on the state transition principles of the three-level system, we propose a statistical model for microwave signal detection.
Wireless Communication Based on Microwave Photon-Level Detection With Superconducting Devices: Achievable Rate Prediction
Future wireless communication system embraces physical-layer signal detection with high sensitivity, especially in the microwave photon level.
Weak Radio Frequency Signal Detection Based on Piezo-Opto-Electro-Mechanical System: Architecture Design and Sensitivity Prediction
We propose a novel radio-frequency (RF) receiving architecture based on micro-electro-mechanical system (MEMS) and optical coherent detection module.
Semi-Federated Learning
Federated learning (FL) enables massive distributed Information and Communication Technology (ICT) devices to learn a global consensus model without any participants revealing their own data to the central server.
