Shaoyang Wang

Orcid: 0000-0001-9801-6913

According to our database1, Shaoyang Wang authored at least 15 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Review on the key technologies of power grid cyber-physical systems simulation.
IET Cyper-Phys. Syst.: Theory & Appl., March, 2024

Shock-Tolerated Multi-Range Low-Noise Analog Front End for Lightning Current Measurements From Milliamperes to Hundreds of Kiloamperes.
IEEE Trans. Instrum. Meas., 2024

2023
A New FDTD Model for Lightning Return Stroke Channel Above Lossy Ground and Its Validation With Rocket-Triggered Lightning Data.
IEEE Access, 2023

Shock Tolerated Low Noise Analog Front-End for Milliamp Measurement on a Low Resistance Shunt.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2023

2022
Multiagent Deep Reinforcement Learning for Cost- and Delay-Sensitive Virtual Network Function Placement and Routing.
IEEE Trans. Commun., 2022

Multi-Agent Deep Reinforcement Learning for Cost- and Delay-Sensitive Virtual Network Function Placement and Routing.
CoRR, 2022

Multi-Agent Deep Reinforcement Learning for Uplink Power Control in Multi-Cell Systems.
Proceedings of the 2022 IEEE International Conference on Communications Workshops, 2022

SNNet: Specific Node Network of Human Parsing.
Proceedings of the Artificial Neural Networks and Machine Learning - ICANN 2022, 2022

2021
Joint Resource Management for MC-NOMA: A Deep Reinforcement Learning Approach.
IEEE Trans. Wirel. Commun., 2021

2020
Learning-Based Multi-Channel Access in 5G and Beyond Networks With Fast Time-Varying Channels.
IEEE Trans. Veh. Technol., 2020

Dynamic Multichannel Access for 5G and Beyond with Fast Time-Varying Channel.
Proceedings of the 2020 IEEE International Conference on Communications, 2020

2019
Optical and Current Measurements of Lightning Attachment to the 356-m-High Shenzhen Meteorological Gradient Tower in Southern Coastal Area of China.
IEEE Access, 2019

Deep Reinforcement Learning Based Dynamic Multichannel Access in HetNets.
Proceedings of the 2019 IEEE Wireless Communications and Networking Conference, 2019

Multi-Agent Reinforcement Learning-Based User Pairing in Multi-Carrier NOMA Systems.
Proceedings of the 17th IEEE International Conference on Communications Workshops, 2019

Deep Reinforcement Learning for Demand-Aware Joint VNF Placement-and-Routing.
Proceedings of the 2019 IEEE Globecom Workshops, Waikoloa, HI, USA, December 9-13, 2019, 2019


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