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The Estimation Performance of Nonlinear Least Squares for Phase Retrieval 期刊论文
IEEE TRANSACTIONS ON INFORMATION THEORY, 2020, 卷号: 66, 期号: 12, 页码: 7967-7977
Authors:  Huang, Meng;  Xu, Zhiqiang
Favorite  |  View/Download:55/0  |  Submit date:2021/04/26
Phase retrieval  estimation performance  nonlinear least squares  nonlinear Lasso  
Consensus of Multi-Agent Systems Under Binary-Valued Measurements and Recursive Projection Algorithm 期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 卷号: 65, 期号: 6, 页码: 2678-2685
Authors:  Wang, Ting;  Zhang, Hang;  Zhao, Yanlong
Favorite  |  View/Download:68/0  |  Submit date:2020/09/23
Convergence  Consensus algorithm  Projection algorithms  Noise measurement  Estimation  Multi-agent systems  Approximation algorithms  Binary-valued communications  convergence  convergence rate  consensus control  estimate  multi-agent systems  recursive projection algorithm  
Performance Output Tracking for Multidimensional Heat Equation Subject to Unmatched Disturbance and Noncollocated Control 期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 卷号: 65, 期号: 5, 页码: 1940-1955
Authors:  Zhou, Hua-Cheng;  Guo, Bao-Zhu;  Xiang, Shu-Huang
Favorite  |  View/Download:90/0  |  Submit date:2020/06/30
Active disturbance rejection control (ADRC)  disturbance rejection  heat equation  output tracking  
Distributed Stochastic Approximation Algorithm With Expanding Truncations 期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2020, 卷号: 65, 期号: 2, 页码: 664-679
Authors:  Lei, Jinlong;  Chen, Han-Fu
Favorite  |  View/Download:78/0  |  Submit date:2020/05/24
Distributed optimization  distributed stochastic approximation  expanding truncation  multiagent network  
Well-Posedness and Finite Element Approximations for Elliptic SPDEs with Gaussian Noises 期刊论文
数学研究通讯:英文版, 2020, 卷号: 36.0, 期号: 002, 页码: 113-127
Authors:  Yanzhao Cao;  Jialin Hong;  Zhihui Liu
Favorite  |  View/Download:100/0  |  Submit date:2021/01/14
Elliptic  stochastic  partial  differential  equation  spectral  approximations  finite  element  approximations  power-law  noise