no code implementations • 17 Apr 2024 • Yaqun Yang, Jinlong Lei, Guanghui Wen, Yiguang Hong
This paper considers a distributed adaptive optimization problem, where all agents only have access to their local cost functions with a common unknown parameter, whereas they mean to collaboratively estimate the true parameter and find the optimal solution over a connected network.
no code implementations • 7 Jan 2024 • Tao Xu, Zhiyong Sun, Guanghui Wen, Zhisheng Duan
This paper revisits the event-triggered control problem from a data-driven perspective, where unknown continuous-time linear systems subject to disturbances are taken into account.
no code implementations • 22 Nov 2023 • Tao Xu, Zhisheng Duan, Guanghui Wen, Zhiyong Sun
This paper studies a challenging issue introduced in a recent survey, namely designing a distributed event-based scheme to solve the dynamic average consensus (DAC) problem.
no code implementations • 21 Sep 2023 • Peihu Duan, Yuezu Lv, Guanghui Wen, Maciej Ogorzałek
Further, the proposed method can be applied to pure fully distributed state estimation scenarios and modified for noise-bounded LTI plants.
no code implementations • 24 May 2023 • Peihu Duan, Tao Liu, Yuezu Lv, Guanghui Wen
Cooperative behavior design for multi-agent systems with collective tasks is a critical issue in promoting swarm intelligence.
no code implementations • 18 Jan 2022 • Zhen Gao, Minghui Wu, Chun Hu, Feifei Gao, Guanghui Wen, Dezhi Zheng, Jun Zhang
To this end, by modeling the key transmission modules as an end-to-end (E2E) neural network, this paper proposes a data-driven deep learning (DL)-based unified hybrid beamforming framework for both the time division duplex (TDD) and frequency division duplex (FDD) systems with implicit channel state information (CSI).
no code implementations • 1 Jul 2020 • Weizhu Qian, Bo-Wei Chen, Yichao Zhang, Guanghui Wen, Franck Gechter
Multi-task learning (MTL) is an important subject in machine learning and artificial intelligence.