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International Conference on Pattern Recognition

作者： Jiehui Deng Sheng Wan Xiang Wang Enmei Tu Xiaolin Huang Jie Yang Chen Gong PCA Lab the Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Hong Kong Polytechnic University Hong Kong SAR China

Estimating the Ratio of Edge-Users (REU) is an important issue in mobile networks, as it helps the subsequent adjustment of loads in different cells. However, existing approaches usually determine the REU manually, which are experience-dependent and labor-intensive, and thus the estimated REU might be imprecise. Considering the inherited graph structure of mobile networks, in this paper, we utilize a graph-based deep learning method for automatic REU estimation, where the practical cells are deemed as nodes and the load switchings among them constitute edges. Concretely, Graph Attention Network (GAT) is employed as the backbone of our method due to its impressive generalizability in dealing with networked data. Nevertheless, conventional GAT cannot make full use of the information in mobile networks, since it only incorporates node features to infer the pairwise importance and conduct graph convolutions, while the edge features that are actually critical in our problem are disregarded. To accommodate this issue, we propose an Edge-Aware Graph Attention Network (EAGAT), which is able to fuse the node features and edge features for REU estimation. Extensive experimental results on two real-world mobile network datasets demonstrate the superiority of our EAGAT approach to several state-of-the-art methods.

关键词： Deep learning Fuses Estimation Switches Pattern recognition

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Multi-View broad learning system for primate oculomotor decision decoding

arXiv

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arXiv 2019年

作者： Shi, Zhenhua Chen, Xiaomo Zhao, Changming He, He Stuphorn, Veit Wu, Dongrui Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Zanvyl Krieger Mind and Brain Institute Johns Hopkins University School of Medicine Department of Neurobiology Stanford University StanfordCA United States Department of Neuroscience Johns Hopkins University BaltimoreMD United States

Multi-view learning improves the learning performance by utilizing multi-view data: data collected from multiple sources, or feature sets extracted from the same data source. This approach is suitable for primate brain state decoding using cortical neural signals. This is because the complementary components of simultaneously recorded neural signals, local field potentials (LFPs) and action potentials (spikes), can be treated as two views. In this paper, we extended broad learning system (BLS), a recently proposed wide neural network architecture, from single-view learning to multi-view learning, and validated its performance in monkey oculomotor decision decoding from medial frontal LFPs and spikes. We demonstrated that medial frontal LFPs and spikes in non-human primate do contain complementary information about the oculomotor decision, and that the proposed multi-view BLS is a more effective approach to classify the oculomotor decision, than several classical and state-of-the-art single-view and multi-view learning approaches. Copyright © 2019, The Authors. All rights reserved.

关键词： Electrophysiology

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A Real-time Framework of Multi-Camera Vehicle Tracking System

A Real-time Framework of Multi-Camera Vehicle Tracking Syste...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Zhuang, Hanyang Chen, Xingyuan Lan, Jianglin Wang, Ying Lu, Zhaoxuan Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200040 China Shanghai Intelligent and Connected Vehicle R and D Center Co. LTD Shanghai201400 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

Multi-camera vehicle tracking (MCVT) system is a key technology to build an intelligent city and intelligent transportation system. The MCVT system utilizes roadside monitoring devices and computing platforms to achieve city-level road traffic perception at a finer scale by tracking each vehicle on the road to obtain the trajectory. The existing MCVT system mainly focuses on dealing with the algorithm modules separately, without studying the real-time performance and system architecture of the entire pipeline. However, in real-world applications, many of the tricks in improving evaluation metrics are not applicable since there is endless traffic flow running all the time. Therefore, this paper proposes a real-time framework of the MCVT system to streamline all the algorithm modules with proper data flow. Firstly, a multi-threaded multi-vehicle tracking (MVT) module is developed to detect vehicles in each camera. Re-identification is implemented during MVT to provide the feature for tracking in the same camera and across different cameras. Then, after the vehicle leaves the camera field of view, the feature of vehicle trajectory is calculated by averaging the feature at each frame. Meanwhile, a background thread runs continuously to match the incoming feature of vehicle trajectory with past features by conducting a topology searching method. In the end, the vehicle trajectories with well-matched features are considered to be the same vehicle. The entire pipeline has been validated on two different datasets, the precision is 0.64 in the CityFlow dataset which uses 6 cameras simultaneously. In the customized dataset, the same method can still reach real-time when using 16 cameras at the same time with smaller network modules. © 2024 IEEE.

关键词： Vehicle locating systems

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Multisensor image adaptive fusion based on nonsubsampled contourlet

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Jisuanji Xuebao/Chinese Journal of Computers 2009年第11期32卷 2227-2238页

作者： Chang, Xia Jiao, Li-Cheng Jia, Jian-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Information Engineering Jingdezhen Ceramic Institute Jingdezhen Jiangxi 333002 China

An adaptive fusion method of multisensor images based on nonsubsampled contourlet transform is proposed in this paper, which can select the fusion weights of the low-frequency coefficients adaptively via golden section algorithm. The nonsubsampled contourlet transform is a flexible multi-scale, multi-direction and shift-invariant image decomposition, which is suitable for representing images bearing abundant detail and directional information. This is employed for fusing the directional high-frequency coefficients. For the directional high-frequency coefficients, the higher adding level of the directional subbands is used to select the better coefficient for fusion. The nonsubsampled contourlet transform can also avoids introducing ringing artifacts to fused images compared to ordinary method. Experimental results show that the proposed method achieves better fusion efficiency compared to image fusion methods based on Laplacian pyramid transform, wavelet transform, stationary wavelet transform and contourlet transform respectively.

关键词： Contourlet transform

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Model-Predictive-control-based Simultaneous Trajectory Tracking and Speed control for intelligent Vehicles*

Model-Predictive-Control-based Simultaneous Trajectory Track...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Hanyang Zhuang Yikai Hu Chunxiang Wang Ming Yang University of Michigan - Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai China Guangxi Key Laboratory of Automobile Components and Vehicle Technology Guangxi University of Science and Technology Liuzhou China Shanghai Jiao Tong University Shanghai Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China

ISBN: (纸本)9781665431545

Trajectory tracking and speed control for intelligent vehicles are put forward higher requirements on accuracy by the high traffic density scenario. A standard Model Predictive control (MPC) algorithm focuses on the trajectory tracking but ignores the speed control. This paper proposes a simultaneous trajectory tracking and speed control algorithm based on MPC approach to address fine control in both space and time dimensions for intelligent vehicles. A threefold cost function including lateral and longitudinal speed as well as comfort has been proposed to improve the control algorithm. The simulations and comparisons demonstrate that the proposed method has a better tracking and speed control performance than the existing method.

关键词： Space vehicles Costs Mechatronics Trajectory tracking intelligent vehicles Velocity control Prediction algorithms

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On Enlarging the Domain of Attraction for Linear Systems Subject to Asymmetric Actuator Saturation

On Enlarging the Domain of Attraction for Linear Systems Sub...

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IEEE Conference on Decision and control

作者： Wenxin Lai Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA U.S.A.

In this paper, we revisit the problem of enlarging the domain of attraction for linear systems with asymmetric actuator saturation. We partition the state space into several regions according to the sign of each input and rewrite the linear system subject to asymmetric actuator saturation as an equivalent switched system, each subsystem of which is associated with one partition of the state space and is a linear system subject to symmetric actuator saturation. Based on this equivalent representation of the system, we present a Lyapunov function, which is composed of a set of quadratic functions associated with matrices that are not required to be positive definite. We establish sufficient conditions for regional stability and, based on them, formulate optimization problems to enlarge the estimate of the domain of attraction. Simulation results illustrate the effectiveness of the proposed approach.

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Joint Observer Gain and Input Design for Asymptotic Active Fault Diagnosis

arXiv

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arXiv 2024年

作者： Xu, Feng Wan, Yiming Wang, Ye Puig, Vicenç Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Ministry of Education China Wuhan430074 China Department of Electrical and Electronic Engineering The University of Melbourne ParkvilleVIC3010 Australia Universitat Politècnica de Catalunya Barcelona08028 Spain

This paper proposes a joint gain and input design method for observer-based asymptotic active fault diagnosis, which is based on a newly-defined notion named the excluding degree of the origin from a zonotope. Using the excluding degree, a quantitative specification is obtained to characterize the performance of set-based robust fault diagnosis. Furthermore, a single gain design method and a joint gain and input design method are proposed, respectively. This is the first work to achieve a joint observer gain and input design for set-based active fault diagnosis. Compared with the existing methods that design gains and input separately, the proposed joint gain and input design method has advantages to exploit the fault diagnosis potential of observer-based schemes. Finally, several examples are used to illustrate the effectiveness of the proposed methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Design

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Fault-Tolerant Consensus for Linear Singular Multi-Agent Systems with Dynamic Adaptive Event-Triggered Mechanism

SSRN

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SSRN 2022年

作者： Jiang, Ping Chen, Jiejie Zeng, Zhigang Chen, Boshan The School of Computer Hubei PolyTechnic University Huangshi435000 China The School of Automation Huazhong University of Science and Technology Wuhan430074 China The College of Computer Science and Technology Hubei Normal University Huangshi435002 China The College of Mathematics and Statistics Hubei Normal University Huangshi435002 China The Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan430074 China

The fault-tolerant consensus of linear singular multi-agent systems (SMASs) is studied in this paper. Firstly, a general dynamic adaptive event-triggered mechanism (ETM) is proposed, and its special cases include the existing dynamic ETM and static ETM. Then, based on this dynamic ETM, a new distributed dynamic adaptive event-triggered fault-tolerant controller (DAETFTC) is designed. Then the consensus problem is discussed for the linear SMASs via the proposed DAETFTC. Moreover, we establish novel sufficient conditions to ensure that all agents of the linear SMAS can reach consensus asymptotically. In addition, it is prove that Zeno behavior can be strictly excluded. Finally, the obtained results are simulated by a numerical example. © 2022, The Authors. All rights reserved.

关键词： Multi agent systems

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An Improved Result on Stabilization of Switched Linear Systems with Time-varying Delay ⁎

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IFAC-PapersOnLine 2021年第18期54卷 96-101页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper revisits the stabilization problem of switched linear systems with time-varying delay via state dependent switching strategies. In contrast to the existing works, the commonly adopted stable convex combination assumption is relaxed in this paper. For switched systems satisfying the relaxed assumption, we design a state dependent switching strategy, under which the considered system is asymptotically stable at the origin in the presence of time-varying delay. An optimization problem is formulated to estimate the upper bound of tolerable time delay. Numerical examples are presented to show that our method is applicable to a larger class of switched systems and leads to greater delay bound.

关键词： Asymptotic stability delay bound state dependent switching switched system time-varying delay

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Distributed Observer Design over Directed Switching Topologies

arXiv

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arXiv 2024年

作者： Xu, Haotian Liu, Shuai Wang, Bohui Wang, Jingcheng School of Control Science and Engineering Shandong University Jinan250061 China The School of Aerospace Science and Technology Xidian University Xi’an710071 China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

The distributed observer design problem holds significant importance in cases in which the output information of a system is decentralized across different subsystems. Each subsystem has a local observer and access to one part of the measurement outputs and information exchanged through communication networks. This paper focuses on the design of distributed observer with jointly connected directed switching networks. The problem presents challenges due to passive switching modes and the open-loop unboundedness that results from local observability. To overcome these challenges, we develop a network transformation mapping method whereby each local observer can classify itself into an independent subgraph based on independent judgment. Next, an observable decomposition and reorganization method is developed for the digraph case to ensure that each subgraph possesses independent dynamic properties. Asymptotic omniscience is then proven using a developed recursive proof method. This paper includes many previous results as special cases, because most are only suitable for undirected switching topologies or fast-switching cases. An adaptive coupling gain design is proposed to simplify the calculation and verification of conditions that guarantee asymptotic omniscience. Finally, simulation results with the power system show the validity of the developed theory. © 2024, CC BY.

关键词： Continuous time systems

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