Search Results - over-the-air+computation

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Methods and Procedures for Synchronization and Over-the-Air Computation
Reference #: 01615 The University of South Carolina is offering licensing opportunities for Methods and Procedures for Synchronization and Over-the-Air Computation Background: Over-the-air computation (OAC) reduces the communication latency that linearly increases with the number of devices in a wireless network for machine learning applications....
Published: 9/18/2023   |   Inventor(s): Alphan Sahin
Keywords(s): federated learning, non-coherent computation, over-the-air computation, software-defined radios, sychronization
Category(s): Software and Computing, Engineering and Physical Sciences
Over-the-Air Computation Methods Based on Balanced Number Systems for FEEL
Reference #: 01612 The University of South Carolina is offering licensing opportunities for Over-the-Air Computation Methods Based on Balanced Number Systems for FEEL Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 10/24/2022   |   Inventor(s): Alphan Sahin
Keywords(s): federated learning, non-coherent computation, over-the-air computation, quantization, signed-digit number system
Category(s): Software and Computing, Engineering and Physical Sciences
Methods for Long-Range Federated Edge Learning with Chirp-Based Over-the-Air Computation
Reference #: 01574 The University of South Carolina is offering licensing opportunities for Methods for Long-Range Federated Edge Learning with Chirp-Based Over-the-Air Computation Background: Federated edge learning (FEEL) deploys federated learning (FL) over a wireless network, in which many edge devices (EDs) participate in training using locally...
Published: 1/3/2023   |   Inventor(s): Safi Shams Muhtasimul Hoque, Alphan Sahin
Keywords(s): chirp, DFT-s-OFDM, Distributed learning, federated edge learning, LoRa, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio, pulse-position modulation
Category(s): Engineering and Physical Sciences, Software and Computing
Methods for Multi-cell Over-the-Air Computation for Distributed Learning
Reference #: 01573 The University of South Carolina is offering licensing opportunities for Methods for Multi-cell Over-the-Air Computation for Distributed Learning Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 5/9/2023   |   Inventor(s): Mohammad Hassan Adeli, Alphan Sahin
Keywords(s): Distributed learning, federated edge learning, frequency-shift keying, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio
Category(s): Engineering and Physical Sciences, Software and Computing
Methods for Reliable Over-the-Air Computation with Pulses for Distributed Learning
Reference #: 01541 The University of South Carolina is offering licensing opportunities for Methods for Reliable Over-the-Air Computation with Pulses for Distributed Learning Background: Federated edge learning (FEEL) is an implementation of federated learning (FL) over a wireless network to train a model by using the local data at the edge devices...
Published: 9/3/2022   |   Inventor(s): Alphan Sahin, Everette Bryson, Safi Shams Muhtasimul Hoque
Keywords(s): DFT-s-OFDM, Distributed learning, federated edge learning, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio, pulse-position modulation, SC-FDE
Category(s): Software and Computing, Engineering and Physical Sciences
Methods for Reliable Over-the-Air Computation and Federated Edge Learning
Reference #: 01538 The University of South Carolina is offering licensing opportunities for Methods for Reliable Over-the-Air Computation and Federated Edge Learning Background: Federated edge learning (FEEL) is a distributed learning framework that leverages the computational powers of edge devices (EDs) and uses the local data at the EDs without...
Published: 9/3/2022   |   Inventor(s): Alphan Sahin, Everette Bryson, Safi Shams Muhtasimul Hoque
Keywords(s): Distributed learning, federated edge learning, frequency-shift keying, orthogonal frequency division multiplexing, over-the-air computation, peak-to-mean envelope power ratio
Category(s): Engineering and Physical Sciences, Software and Computing
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