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Distributed solver for linear matrix inequalities: an optimization perspective

Control Theory and Technology 2021年第4期19卷 507-515页

作者： Weijian Li Wen Deng Xianlin Zeng Yiguang Hong Department of Automation University of Science and Technology of ChinaHefei 230027AnhuiChina Key Lab of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

In this paper,we develop a distributed solver for a group of strict(non-strict)linear matrix inequalities over a multi-agent network,where each agent only knows one inequality,and all agents co-operate to reach a consensus solution in the intersection of all the feasible *** formulation is transformed into a distributed optimization problem by introducing slack variables and consensus ***,by the primal–dual methods,a distributed algorithm is proposed with the help of projection operators and derivative ***,the convergence of the algorithm is analyzed,followed by illustrative simulations.

关键词： Distributed computation Distributed optimization Linear matrix inequalities Primal-dual method

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Photoelectric intelligent Detection Platform Based on Multifunctional Edge Computing Equipment

Photoelectric Intelligent Detection Platform Based on Multif...

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第43届中国控制会议

作者： Qianjing Xu Wenjie Chen Zhijun Xue State Key Lab of Intelligent Control and Decision of Complex Systems

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In order to study to design a photoelectric intelligent platform based on multifunctional edge computing equipment by using photoelectric detection equipment TC505C, RK-Series Development Kits computing platform and Nvidia Jetson *** photoelectric intelligent platform can be used to run multiple target detection algorithms after design and *** as *** of all, after the first stage of the photoelectric intelligent platform is completed, the host computer can establish communication with the photoelectric detection equipment, carry out automatic or manual servo control on the photoelectric detection equipment, switch its visible and infrared field of view and view it in real time through the monitor, and realize simple tracking function through the image processing ***, after the second stage of the photoelectric intelligent platform is built, under the premise of ensuring the normal availability of servo function, a variety of target detection algorithms can be debugged on multifunctional edge computing ***, this paper uses the modular design concept to design, debug and implement the system in stages. Pay attention to the synchronous debugging of hardware and software functions of each module to ensure the stability of each module. Finally completed the design goals of each stage.

关键词： Multifunctional Edge Computing Equipment Photoelectric intelligent Platform Object Detection

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Consensus of First-order Multi-agent systems via Adaptive Event-Based Impulsive Control

Consensus of First-order Multi-agent Systems via Adaptive Ev...

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第37届中国控制会议

作者： Qianghui Zhou Dandan Wang Wei Zhu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications

This paper investigates the consensus problem of first-order multi-agent systems with adaptive event-based impulsive controller. The triggering function based on the states of the agents is designed. The impulsive instants are determined by the triggering function and triggering condition, that is, the impulsive effect performs at the instants when the events occur, and so as the controllers update. It is shown that not only the consensus can be achieved without the continue communication between neighboring agents but also the global information/parameters of the concerned closed-loop system are avoided. Moreover,the Zeno-behavior is excluded for the concerned closed-loop system. Finally, a numerical example is provided to illustrate the effectiveness of the obtained theoretical results.

关键词： Multi-agent systems Consensus Adaptive Event-based Impulsive

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Exponential p-stability of stochastic impulsive fuzzy reaction-diffusion Cohen-Grossberg neural networks with mixed delays

Exponential p-stability of stochastic impulsive fuzzy reacti...

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第34届中国控制与决策会议

作者： Weisong Zhou Sa Xiao Wei Zhu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications

In this paper,the pth moment exponential stability of a class of stochastic impulsive fuzzy reaction-diffusion Cohen-Grossberg neural networks(CGNNs) with mixed delays is *** means of the property of "M-cone",Lyapunov functional,Ito formula and Hanalay inequality techniques,sufficient conditions for exponential p-stability of our model are ***,a simulation example is given to verify the validity of our result.

关键词： Exponential stability Cohen-Grossberg Mixed delays Impulsive Fuzzy

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pth input-to-state stability of stochastic bidirectional associative memory neural networks with infinite delays

pth input-to-state stability of stochastic bidirectional ass...

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第40届中国控制会议

作者： Weisong Zhou Shi Dan Jiachang Chen Wei Zhu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications

In this paper, bidirectional associative memory neural networks（BAMNNs） with infinite delays under the influence of Brownian motion or Markovian switching are investigated respectively. By utilizing It? formula and constructing new Halanay differential inequalities, two sufficient conditions ensuring the pth input-to-state stability（p-ISS） of the neural networks are obtained. A numerical example is given to illustrate the efficiency of the derived results.

关键词： Input-to-state stability BAM neural networks Brownian motion Markovian switching Infinite delays

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Global attracting set and asymptotic behavior for a class of impulsive functional Hopfield neural networks by a novel vector inequality

Global attracting set and asymptotic behavior for a class of...

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第35届中国控制与决策会议

作者： Weisong Zhou Guihua Li Wei Zhu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications

This article is concerned with a class of nonlinear and nonautonomous functional Hopfield neural networks with impulsive *** existence of attracting set and invariant set of the desired impulsive differential equations is ***,we construct a novel vector inequality,which considers the features of *** on the more general vector inequality,we ensure the positive invariant set and global attracting set for a class of the impulsive functional differential *** means of numerical simulation,the effectiveness of our theoretical results is demonstrated.

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Bearing-only Formation of Multi-agent systems via Edge-based Event-triggered Control

Bearing-only Formation of Multi-agent Systems via Edge-based...

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第42届中国控制会议

作者： Chenjun Liu Wei Zhu Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications

The event-triggered bearing-only formation of leader-following multi-agent systems is studied in this paper. Based on the neighboring bearing information at event-triggering time instants, the edge-based event-triggered scheme for stationary formation is designed. The event-triggering time instants are iteratively determined by a combined technique, where the Zenobehavior can be avoided directly. A sufficient condition for achieving formation is presented under the assumption that there is no collision among agents. Finally, the numerical simulation is given to illustrate the effectiveness of the theoretical results.

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From Unmanned systems to Autonomous intelligent systems

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Engineering 2022年第5期8卷 16-19页

作者： Jie Chen Jian Sun Gang Wang Department of Control Science and Engineering Tongji UniversityShanghai 201804China Shanghai Research Institute for Intelligent Autonomous Systems Shanghai 200092China Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China

*** Artificial intelligence(AI)is a rapidly growing field of technol-ogy,which“will enliven inert objects,much as electricity did more than a century *** that we formerly electrified will now cognitize”[1].AI advances are constantly pushing the frontier of what machines can *** attention is being placed on AI research,as well as its development and deployment by commer-cial investors,defense strategists,and policy makers[2].

关键词： frontier inert policy

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An efficient framework for sentence similarity inspired by quantum computing 12

An efficient framework for sentence similarity inspired by q...

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12th IEEE International Conference on Big Knowledge, ICBK 2021

作者： Yu, Yan Qiu, Dong Yan, Ruiteng Chongqing University of Posts and Telecommunications School of Computer Science and Technology Nan'an Chongqing400065 China Key Laboratory of Intelligent Analysis and Decision On Complex Systems Chongqing University of Posts and Telecommunications Nan'an Chongqing400065 China

ISBN: (纸本)9781665438582

Accurately extracting the semantic information and the syntactic structure of sentences is important in natural language processing. Existing methods mainly combine the dependency tree to deep learning with complex computation time to achieve enough semantic information. It is essential to obtain sufficient semantic information and syntactic structures without any prior knowledge excepting word2vec. This paper proposes a model on sentence representation inspired by quantum entanglement using the tensor product to entangle both two consecutive notional words and words with depen-dencies. Inspired by quantum entanglement coefficients, we construct two different entanglement coefficients to weight the different semantic contributions of words with different relations. Finally, the proposed model is applied to SICK_train to verify their performances. The experimental results show that the provided methods achieve perfect results. © 2021 IEEE.

关键词： Quantum entanglement

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Data-Driven Discovery of Nonlinear Dynamical systems from Noisy and Sparse Observations

Data-Driven Discovery of Nonlinear Dynamical Systems from No...

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2024 International Conference on New Trends in Computational Intelligence, NTCI 2024

作者： Zhu, Wei Pei, Chao Liang, Yulan Chen, Zhang Li, Jingsui School of Science Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing China College of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (纸本)9798331517021

Sparse Identification of Nonlinear Dynamics (SINDy) is a data-driven algorithm for interpretability mod-eling. SINDy has a strong ability to learn dynamical systems from time series data. Sparse Identification of Nonlinear Dynamics (SINDy) can extract equations from data, but its performance will degrade when data has noise or sparse. In order to deal with this case, the idea of Monte Carlo Markov Chain (MCMC) is introduced, which is used to optimally select models. The SINDy with MCMC (MCMC-SINDy) can comprehensively discover model structures by employing random samples in data space. Simulation results show that MCMC-SINDy is more robust than SINDy with 1 % -15 % levels of noise or sparse 0.5. These results are promising for the discovery of governing equations for complex systems in neuroscience, power grids, epidemiology, finance or ecology, where governing equations have remained elusive. mportantly, compared to existing machine learning methods, the accuracy of modeling using MCMC SINDy is higher. © 2024 IEEE.

关键词： Markov chains

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