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厦门大学 [5]
半导体研究所 [5]
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Influence of finite coherence of injected light on ring-down cavity measurement method and intensity integral method for ring-down time determination
期刊论文
ACTA PHYSICA SINICA, 2023, 卷号: 72, 期号: 18, 页码: 10
作者:
Huang, Zhi-Qiu
;
Zhang, Meng
;
Peng, Zhi-Min
;
Wang, Zhen
;
Yang, Qian-Suo
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2023/11/28
cavity ring-down spectroscopy
light coherence
ring-down time
intensity integration
A Data-Driven Iterative Learning Approach for Optimizing the Train Control Strategy
期刊论文
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2023, 卷号: 19, 期号: 7, 页码: 7885-7893
作者:
Su, Shuai
;
Zhu, Qingyang
;
Liu, Junqing
;
Tang, Tao
;
Wei, Qinglai
收藏
  |  
浏览/下载:2/0
  |  
提交时间:2023/11/17
Deep reinforcement learning (RL)
driving strategy
energy-efficient train control (EETC)
soft actorcritic (SAC)
Distributed Dynamic Event-Triggered Control for Euler-Lagrange Multiagent Systems With Parametric Uncertainties
期刊论文
IEEE TRANSACTIONS ON CYBERNETICS, 2021, 页码: 13
作者:
Cao, Ran
;
Cheng, Long
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  |  
浏览/下载:34/0
  |  
提交时间:2022/01/27
Vehicle dynamics
Nonlinear dynamical systems
Symmetric matrices
Laplace equations
Heuristic algorithms
Directed graphs
Robot sensing systems
Consensus
containment
dynamic event-triggered control
Euler-Lagrange system
multiagent systems (MASs)
Applying Knowledge Inference on Event-Conjunction for Automatic Control in Smart Building
期刊论文
APPLIED SCIENCES-BASEL, 2021, 卷号: 11, 期号: 3, 页码: 17
作者:
Ge, Hangli
;
Peng, Xiaohui
;
Koshizuka, Noboru
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  |  
浏览/下载:20/0
  |  
提交时间:2021/12/01
smart building
Internet of Things (IoT)
Markov Chain Monte Carlo (MCMC)
ontology
graph model
Completely distributed neuro-learning consensus with position constraints and partially unknown control directions
期刊论文
Neurocomputing, 2020, 卷号: 418, 页码: 251-262
作者:
Yang, Nana
;
Li, Junmin
;
He, Chao
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  |  
浏览/下载:5/0
  |  
提交时间:2020/11/14
Iterative methods
Composite energy function
Control directions
Distributed learning
Finite time intervals
Nonlinear multi-agent systems
Nussbaum functions
Simulation example
Unknown control direction
Fully distributed hybrid adaptive learning consensus protocols for a class of non-linearly parameterized multi-agent systems
期刊论文
Applied Mathematics and Computation, 2020, 卷号: 375
作者:
Yang, Nana
;
Li, Junmin
;
Chen, Jiaxi
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  |  
浏览/下载:5/0
  |  
提交时间:2020/11/14
Adaptive control systems
Iterative methods
Learning systems
Parameterization
Consensus problems
Consensus protocols
Finite time intervals
Fully distributed
Krasovskii functional
Parameterized
Separation techniques
Simulation example
Bulk properties of the system formed in Au plus Au collisions at root S-NN=14.5 GeV at the BNL STAR detector
期刊论文
PHYSICAL REVIEW C, 2020, 卷号: 101, 期号: 2, 页码: 25
作者:
Adam, J.
;
Adamczyk, L.
;
Adams, J. R.
;
Adkins, J. K.
;
Agakishiev, G.
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  |  
浏览/下载:18/0
  |  
提交时间:2022/01/18
Bulk properties of the system formed in Au plus Au collisions at root S-NN=14.5 GeV at the BNL STAR detector
期刊论文
PHYSICAL REVIEW C, 2020, 卷号: 101, 期号: 2, 页码: -
作者:
Adam, J
;
Adamczyk, L
;
Adams, JR
;
Adkins, JK
;
Agakishiev, G
收藏
  |  
浏览/下载:60/0
  |  
提交时间:2021/09/06
NUCLEUS-NUCLEUS COLLISIONS
TIME PROJECTION CHAMBER
QUARK-GLUON PLASMA
PARTICLE IDENTIFICATION
FINITE-TEMPERATURE
QCD
ENERGY
DEPENDENCE
MODEL
PERSPECTIVE
Distributed robust adaptive learning coordination control for high-order nonlinear multi-agent systems with input saturation
期刊论文
IEEE Access, 2020, 卷号: 8, 页码: 9953-9964
作者:
Yang, Nana
;
Li, Junmin
收藏
  |  
浏览/下载:3/0
  |  
提交时间:2020/11/14
Adaptive control systems
Iterative methods
Learning systems
Adaptive coordination
Distributed protocols
Finite time intervals
Initial state learning
Input saturation
Iterative learning control
Nonlinear multi-agent systems
Parameter adaptive laws
Distributed iterative learning coordination control for leader-follower uncertain nonlinear multi-agent systems with input saturation
期刊论文
IET Control Theory and Applications, 2019, 卷号: 13, 期号: 14, 页码: 2252-2260
作者:
Yang, Nana
;
Li, Junmin
收藏
  |  
浏览/下载:1/0
  |  
提交时间:2020/11/14
Adaptive control systems
Distributed parameter control systems
Learning systems
Adaptive iterative learning
Coordination control
Distributed control protocols
Finite time intervals
Formation control problems
Initial conditions
Iterative learning
Nonlinear multi-agent systems
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