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检索条件"机构=Key Lab of Intelligent Analysis and Decision on Complex Systems"

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An Existence Result for the Hénon Equation with Critical Exponent 3

An Existence Result for the Hénon Equation with Critical Ex...

引用

3rd International Conference on Applied Mathematics, Modelling, and intelligent Computing, CAMMIC 2023

作者： Huili, Yifeng Deng, Zhi-Ying School of Science Chongqing University of Posts and Telecommunications Chongqing400065 China Key Lab of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing400065 China

In this paper, we study the existence of positive solutions for a Hénon elliptic system with boundary value problems involving the critical exponent. Based upon the variational methods, we prove the existence of ... 详细信息

ISBN: (数字)9781510667617

ISBN: (纸本)9781510667600

关键词： Boundary value problems

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Distilling Siamese Trackers with Attention Mask 41

Distilling Siamese Trackers with Attention Mask

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第41届中国控制会议

作者： Han Sun Yongqiang Bai Wenbo Zhang State Key Lab of Intelligent Control and Decision of Complex Systems and School of Automation Beijing Institute of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In recent years,the introduction of Siamese network has brought new vitality to the object tracking ***,high-performance Siamese trackers cannot run at a real-time speed on mobile devices due to their complex and huge *** distillation is a common and effective model compression method,but it is difficult to be applied to the challenging task like object *** find out the fundamental cause is that the imbalance between the foreground and background in the object tracking task,which aggravates the problem of insufficient feature extraction ability of small ***,we propose the attention mask distillation(AMD) to help the student tracker focus on the foreground area faster and more *** attention mask can be easily obtained from the feature maps and brings fine-granularity to the traditional binary *** experimental results on OTB100 and VOT2018 show that our method enables the student tracker perform as well as the teacher *** the same time,it's able to run on the CPU at a hyper-real-time of 66 fps and achieves nearly 9 times model compression *** low computational and storage costs make it possible to deploy high-performance trackers on resource-constrained platforms.

关键词： Object Tracking Siamese Network Knowledge Distillation Attention Mask

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Model Reconstruction Based on Physical-Informed Polynomial Neural ODEs 13

Model Reconstruction Based on Physical-Informed Polynomial N...

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13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： Chen, Zhang Zhu, Wei Li, Jingsui Bian, Hanlin Pei, Chao School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China Chongqing University of Posts and Telecommunications Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing400065 China

ISBN: (纸本)9798350361674

Neural networks are capable function approximators for data, but their lack of interpretability poses challenges. Physical-informed Polynomial Neural Ordinary Differential Equations (PIPNODEs) are proposed. They combine the constraints of prior knowledge of the data with interpretable Polynomial Neural Ordinary Differential Equations (PolyNODEs) to discover or approximate the governing equations. In this work, Neural Ordinary Differential Equations (NODEs) are categorized into two layers: a physical-informed term, which represents the priori knowledge of the data, and a discrepancy term, which is derived from the approximation of PolyNODEs. Pruning strategies are also used to remove redundant terms with coefficients lower than a certain threshold. We demonstrate the effectiveness and flexibility of this framework in a series of numerical algorithms with varying levels of prior knowledge. We found that having correct but incomplete physical information accelerates training and approaching thresholds compared to having incorrect physical information. © 2024 IEEE.

关键词： data modeling discprepancy modeling interpretability Neural Ordinary Differential Equations physics-informed machine learning polynomial neural network

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Parameter Inversion of High-Dimensional Chaotic systems Using Neural Ordinary Differential Equations 13

Parameter Inversion of High-Dimensional Chaotic Systems Usin...

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13th IEEE Data Driven Control and Learning systems Conference, DDCLS 2024

作者： Bian, Hanlin Zhu, Wei Chen, Zhang Jingsui, L. Pei, Chao Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing400065 China School of Computer Science and Technology Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9798350361674

High-dimensional chaotic systems possess complex structural characteristics, which have potential research value in fields like encrypted communication and chaos control. The inverse problem of parameters in high-dimensional chaotic systems is of significant importance for a profound understanding of the dynamic properties of such systems. This article takes a departure from neural ordinary differential equations and embeds the structural dynamics of the dynamical systems to the parameter inversion of high-dimensional chaotic systems. Numerical experiments on different high-dimensional chaotic systems indicate that neural ordinary differential equations perform exceptionally well in solving these inversion problems, with low errors and strong robustness. © 2024 IEEE.

关键词： Inverse problems

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

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

引用

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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Interpretable Fourier Neural Ordinary Differential Equations

Interpretable Fourier Neural Ordinary Differential Equations

引用

Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Hanlin Bian Wei Zhu Zhang Chen Jingsui Li Chao Pei Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

Numerous interacting elements can form complex systems. However, describing complex systems is extremely challenging and lacks interpretability. The construction of models still heavily relies on scientists’ understanding of complex systems. This paper explores the use of neural ordinary differential equations in the field of complex system modeling. The proposed Fourier neural ordinary differential equations offer interpretability and a relatively simple structure. By building upon interpretable modeling, the scale is significantly reduced. It is possible to deduce the system’s expression from the model’s parameters. Finally, a real-world system is provided to illustrate the effectiveness of the proposed model, demonstrating its commendable robustness.

关键词： Training Atmospheric modeling Fitting Time series analysis Ordinary differential equations Predictive models Mathematical models

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Time-Varying Formation Control for Multiagent systems with Different Time Delays 9

Time-Varying Formation Control for Multiagent Systems with D...

引用

9th International Conference on Fuzzy systems and Data Mining, FSDM 2023

作者： Sun, Fenglan Liang, Qinbo Zhu, Wei Li, Qiuying Key Lab of Intelligent Analysis and Decision on Complex Systems School of Science Chongqing University of Posts and Telecommunications Chongqing400065 China Key Laboratory of Intelligent Air-Ground Cooperative Control for Universities in Chongqing College of Automation Chongqing University of Posts and Telecommunications Chongqing400065 China

ISBN: (纸本)9781643684703

This article studies the time-varying formation (TVF) problem of multiagent systems (MASs) with different time delays. By designing the control protocol, the followers could achieve the desired TVF. Considering different communication delays, based on graph theory and stability theory, sufficient conditions for the system to realize TVF are obtained. Finally, the numerical example is employed to validate the effectiveness of theoretical results. © 2023 The authors and IOS Press.

关键词： Multi agent systems

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Containment Control of Fractional-order Nonlinear Multi-agent systems with Time Delay

Containment Control of Fractional-order Nonlinear Multi-agen...

引用

Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Yanqiu Li Wei Zhu Bo Chen Key Laboratory of Intelligent Analysis and Decision on Complex Systems Chongqing University of Posts and Telecommunications Chongqing China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

Formation control of multi-agent systems is an extension of its consensus problem, which has been widely used in control science and engineering, system science, information and communication engineering and other disciplines. Compared with using integral-order calculus to describe the change of the state of the object, the fractional-order calculus can represent and reflect the real physical characteristics of the object better. In this paper, containment control problem of fractional-order nonlinear multi-agent systems with time delay is studied. In spite of the difficulties and challenges caused by the operator complex property and system delay in fractional-order calculus, this paper solves the containment control problem by constructing a quadratic Lyapunov function and using matrix analysis theory, graph theory and fractional Razumikhin method. The conditions of linear matrix inequalities for asymptotically containment control are given. Finally, numerical simulation results verify the effectiveness of the proposed control scheme.

关键词： Delay effects Control systems Numerical simulation Calculus Graph theory Formation control Linear matrix inequalities

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Boosting Black-Box Adversarial Attacks with Meta Learning 41

Boosting Black-Box Adversarial Attacks with Meta Learning

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第41届中国控制会议

作者： Junjie Fu Jian Sun Gang Wang Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing Institute of Technology Chongqing Innovation Center

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Deep neural networks(DNNs) have achieved remarkable success in diverse ***,it has been demonstrated that DNNs are very vulnerable to adversarial examples even in black-box settings.A large number of black-box attack methods have been proposed to in the ***,those methods usually suffer from low success rates and large query counts,which cannot fully satisfy practical *** this paper,we propose a hybrid attack method which trains meta adversarial perturbations(MAPs) on surrogate models and performs black-box attacks by estimating gradients of the *** method uses the meta adversarial perturbation as an initialization and subsequently trains any black-box attack method for several ***,the MAPs enjoy favorable transferability and universality,in the sense that they can be employed to boost performance of other black-box adversarial attack *** experiments demonstrate that our method can not only improve the attack success rates,but also reduces the number of queries compared to other methods.

关键词： Deep neural networks adversarial examples black-box attack meta adversarial perturbation transferability

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