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Event-triggered distributed state estimation with randomly occurring uncertainties and nonlinearities over sensor networks: A delay-fractioning approach

机译：传感器网络随机发生的不确定性和非线性的事件触发分布式状态估计：延迟分数方法

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Jun Hu; Zidong Wang; Jinling Liang; Hongli Dong;
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年度 2015
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1. Event-triggered distributed state estimation with randomly occurring uncertainties and nonlinearities over sensor networks: A delay-fractioning approach [J] . Hu Jun, Wang Zidong, Liang Jinling, Journal of the Franklin Institute . 2015,第9期

机译：事件触发的分布状态估计，其在传感器网络上具有随机发生的不确定性和非线性：一种延迟分数方法
2. Finite-time event-triggered non-fragile state estimation for discrete-time delayed neural networks with randomly occurring sensor nonlinearity and energy constraints [J] . Neurocomputing . 2020,第Apra7期

机译：具有随机发生的传感器非线性和能量约束的离散时间延迟神经网络的有限时间事件触发非脆弱状态估计
3. Event-triggered non-fragile state estimation for delayed neural networks with randomly occurring sensor nonlinearity [J] . Zha Lijuan, Fang Jian-an, Liu Jinliang, Neurocomputing . 2018,第jana17期

机译：具有随机发生的传感器非线性的延迟神经网络的事件触发非脆弱状态估计
4. Distributed fault estimation for time-varying systems with randomly occurring nonlinearities over sensor networks [C] . Xianye Bu, Hongli Dong, Weijian Ren, Chinese Control Conference . 2016

机译：传感器网络上随机发生非线性的时变系统的分布式故障估计
5. Distributed estimation in sensor networks with modeling uncertainty [D] . Zhou, Qing 2013

机译：具有建模不确定性的传感器网络中的分布式估计
6. Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts [O] . Yunji Li, Li Peng 2018

机译：随机发生的传感器非线性和丢包情况的多跳中继网络上随机系统的事件触发故障估计
7. Event-Triggered Fault Estimation for Stochastic Systems over Multi-Hop Relay Networks with Randomly Occurring Sensor Nonlinearities and Packet Dropouts [O] . Yunji Li, Li Peng 2018

机译：随机发生传感器非线性和数据包丢弃器的多跳中继网络随机系统的事件触发故障估计
8. Distributed Estimation in Sensor Networks with Imperfect Model Information: An Adaptive Learning-Based Approach. [R] . Zhou, Q., Kar, S., Huie, L., 2012

机译：基于不完全模型信息的传感器网络分布式估计：一种基于自适应学习的方法。

Event-triggered distributed state estimation with randomly occurring uncertainties and nonlinearities over sensor networks: A delay-fractioning approach

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