Dynamic Quantum Federated Learning for Satellite-Ground Integrated Systems Using Slimmable Quantum Neural Networks-Reference-Cited by-同舟云学术

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Dynamic Quantum Federated Learning for Satellite-Ground Integrated Systems Using Slimmable Quantum Neural Networks

Published:2024 Issue: Volume:12 Page:58239-58247
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Park Soohyun¹^ORCID,Jung Soyi²^ORCID,Kim Joongheon³^ORCID

Affiliation:

1. Division of Computer Science, Sookmyung Women’s University, Seoul, Republic of Korea

2. Department of Electrical and Computer Engineering, Ajou University, Suwon, Republic of Korea

3. Department of Electrical and Computer Engineering, Korea University, Seoul, Republic of Korea

Funder

Institute of Information and Communications Technology Planning and Evaluation

Korean Government the Ministry of Science and Information and Communications Technology (MSIT), Information and Communications Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10506692.pdf?arnumber=10506692

Reference44 articles.

1. Controlling Antenna Sidelobe Radiation to Mitigate Ku-Band LEO-to-GEO Satellite Interference

2. Reliable Uplink Synchronization Maintenance for Satellite-Ground Integrated Vehicular Networks: A High-Order Statistics-Based Timing Advance Update Approach

3. Stabilized Detection Accuracy Maximization Using Adaptive SAR Image Processing in LEO Networks

4. A Satellite Handover Strategy Based on the Potential Game in LEO Satellite Networks

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