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A Note on the Convergence of Distributed RLS 期刊论文
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2022, 卷号: 67, 期号: 12, 页码: 6762-6769
作者:  Liu, Zhaobo;  Li, Chanying
收藏  |  浏览/下载：83/0  |  提交时间：2023/02/07
Distributed estimation  mean square convergence  noises  recursive least squares  strong consistency  
Distributed system identification for linear stochastic systems with binary sensors 期刊论文
AUTOMATICA, 2022, 卷号: 141, 页码: 13
作者:  Fu, Kewei;  Chen, Han-Fu;  Zhao, Wenxiao
收藏  |  浏览/下载：80/0  |  提交时间：2023/02/07
Distributed system identification  Binary-valued sensor  Stochastic approximation  Consensus  Convergence  Strong consistency  
An adaptive group LASSO approach for domain selection in functional generalized linear models 期刊论文
JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2022, 卷号: 219, 页码: 13-32
作者:  Sun, Yifan;  Wang, Qihua
收藏  |  浏览/下载：122/0  |  提交时间：2022/06/21
Functional data  Adaptive LASSO  Group LASSO  Null region detection  B-spline  

Identification and adaptation with binary-valued observations under non-persistent excitation condition

 期刊论文
AUTOMATICA, 2022, 卷号: 138, 页码: 9
作者:  Zhang, Lantian;  Zhao, Yanlong;  Guo, Lei
收藏  |  浏览/下载：61/0  |  提交时间：2023/02/07
Binary-valued observation  Quasi-Newton algorithm  Identification  Persistent excitation  Martingales  Adaptation  
Distributed Filter With Biased Measurements: A Scalable Bias-Correction Approach 期刊论文
IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS, 2022, 卷号: 8, 页码: 844-854
作者:  Zhang, Xiaocheng;  Xue, Wenchao;  He, Xingkang;  Fang, Haitao
收藏  |  浏览/下载：99/0  |  提交时间：2023/02/07
State estimation  Kalman filters  Estimation  Symmetric matrices  Robot sensing systems  Scalability  Observability  Sensor network  measurement bias  bias estimator  distributed filter  
DISTRIBUTED ORDER ESTIMATION OF ARX MODEL UNDER 期刊论文
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 2022, 卷号: 60, 期号: 3, 页码: 1519-1545
作者:  Gan, D. I. E.;  Liu, Zhixin
收藏  |  浏览/下载：211/0  |  提交时间：2023/02/07
distributed order estimation  cooperative excitation condition  distributed least squares  convergence