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Consensus in second-order multi-agent systems via impulsive control using position-only information with heterogeneous delays

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IET control Theory and Applications 2015年第3期9卷 336-345页

作者： Wang, Yan-Wu Yi, Jing-Wen School of Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science AndTechnology Ministry of China China

This study investigates the consensus problem of second-order multi-agent systems (MASs) via impulsive control using position-only information with communication delays. The communication delays between any two distinct agents are different which can be larger than one impulsive period. A distributed impulsive consensus protocol is designed, in which only the delayed sampled relative positions to neighbours and the relative position to the last sampling state are utilised. By introducing some virtual subgraphs and performing three steps of model transformation, the consensus problem of original continuous-time system is converted to the stability problem of a discrete-time expanded error system. Some necessary and sufficient criteria are derived to grantee the dynamic average-consensus of the MAS. Furthermore, a special case, that is, the delays less than one impulsive period, is discussed, and the bounds of impulsive periods for the dynamic average-consensus are obtained in explicit expressions for both the undirected and directed communication graphs, respectively. Two numerical simulation examples are given to illustrate the effectiveness of theoretical results. © 2015 The Institution of Engineering and Technology.

关键词： Multi agent systems

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Object tracking in infrared image sequence by Monte-Carlo method

Object tracking in infrared image sequence by Monte-Carlo me...

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International Congress on image and Signal processing

作者： Ma, Qianli Wang, Min Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan China Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan China

ISBN: (纸本)9781424465149

This paper presents a robust tracking algorithm for infrared objects in the image sequence, which is based on particle filer. Particle filter is a powerful tool for tracking especially in non-Gaussian condition, but the selection of samples is still a challenging problem. According to the frame-to-frame correlation, two basic assumptions are proposed. Borrowing the idea from Sequence Importance Sampling, Monte-Carlo method will be applied to solve the well-known shortcomings of Particle filter in this paper. Technologically, the proposed algorithm could also track multiple objects successfully. The experimental result has demonstrated its feasibility and validity. ©2010 IEEE.

关键词： Infrared imaging

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A new constrained spectral clustering for SAR image segmentation

A new constrained spectral clustering for SAR image segmenta...

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2009 Asia-Pacific Conference on Synthetic Aperture Radar, APSAR 2009

作者： Zou, Haishuang Zhou, Weida Zhang, Li Wu, Caili Liu, Ruochen Jiao, Licheng Institute of Intelligent Information Processing Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Xidian University 710071 China

ISBN: (纸本)9781424427314

Pairwise constraints have been successful to be applied in traditional clustering methods. However, little progress has been made in incorporating them into spectral clustering. In this paper, we propose a new method to combine pairwise constraints with spectral clustering and apply it to SAR image segmentation. Firstly, we learn a distance metric using pairwise constraints. In doing so, an affinity matrix is obtained by the Gaussian function on the learned distance metric. Then we perform the spectral decomposition on the affinity matrix and we get the spectral features of data points. Finally, the constrained k-means is used to cluster spectral features instead of k-means used commonly. We apply the proposed method to synthetic aperture radar (SAR) image segmentation. Experimental results show that it is effective for SAR image segmentation. ©2009 IEEE.

关键词： image segmentation

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Improved taboo search algorithm for designing DNA sequences

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Progress in Natural Science:Materials International 2008年第5期18卷 623-627页

作者： Kai Zhang a, Jin Xu a,b, Xiutang Geng a, Jianhua Xiao a, Linqiang Pana, a The key laboratory of image processing and intelligent control, Department of control Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China b School of Electronic Engineering and Computer Science, Peking University, Beijing 100871, China The Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China School of Electronic Engineering and Computer Science Peking University Beijing 100871 China

The design of DNA sequences is one of the most practical and important research topics in DNA computing. We adopt taboo search algorithm and improve the method for the systematic design of equal-length DNA sequences, which can satisfy certain combinatorial and thermodynamic constraints. Using taboo search algorithm, our method can avoid trapping into local optimization and can nd a set of good DNA sequences satisfying required constraints.

关键词： DNA computing Taboo search algorithm DNA sequence design

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image retrieval using the modified intersecting cortical model

Image retrieval using the modified intersecting cortical mod...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Yuan, Wenjin Zhang, Xuming School of Life Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769546230

The intersecting cortical model(ICM) is driven from the pulse-coupled neural networks (PCNN), and a lot of works have been done on it. In this paper, we have proposed a method, which is modified from the PCNN, to retrieval the image. This method uses the iteration times of the ICM as the feature, and we do it repeatedly. So we will get the feature vectors and utilize the features to retrieval the image. And the experimental results have proved the effectiveness of the proposed method. While the proposed method shows some advantages like the feature curves are linear and steady. © 2011 IEEE.

关键词： image retrieval

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Cognitive Navigation for intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

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Cross-user Gesture Recognition Based on Deep Domain Adaptation Networks 43

Cross-user Gesture Recognition Based on Deep Domain Adaptati...

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43rd Chinese control Conference, CCC 2024

作者： Fu, Zhongzheng He, Xinrun Wang, Haoyuan Chen, Xingjian Li, Yixuan Huang, Jian Huazhong University of Science and Technology Ministry of Education Key Laboratory of Image Processing and Intelligent Control Hubei Key Laboratory of Brain-inspired Intelligent Systems School of Artificial Intelligence and Automation Wuhan430074 China

ISBN: (纸本)9789887581581

This study introduces an innovative approach for gesture recognition in smart wearable devices using a deep domain adaptation model, focusing on the challenges posed by heterogeneous user environments and the need for precise, adaptable, and personalized gesture recognition systems. Traditional methods based on machine learning and deep learning techniques, while effective, struggle with the variance in data distribution among different users, leading to accuracy challenges. To address this, the study proposes the Domain Kernel-Alignment Adaptation Network (DKAN) model, utilizing a new Kernel-Aligned Multi-kernel Maximum Mean Discrepancy (KAMMD) method within deep networks. By calculating kernel alignments between source and target domains and adjusting weights of Gaussian kernels accordingly, DKAN emphasizes features conducive to transfer learning, enabling more accurate cross-user gesture recognition. The model achieves a significant average accuracy of 97.3% across 21 gestures, highlighting its potential in practical applications. This advancement addresses challenges in traditional gesture recognition methods and sets a new direction for future research in smart wearable technology. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Adversarial machine learning

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An overview about pinning control of complex networks

An overview about pinning control of complex networks

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Chen, Xi Zhang, Lan Li, Wei Institute of System Engineering Huazhong University of Science and Technology Image Processing Ministry of China Wuhan Hubei 430074 China Department of Control Science and Engineering Image Processing and Intelligent Control Key Laboratory Education Ministry of China China

ISBN: (纸本)9780956715715

Synchronization and pinning control of complex networks is to regulate the agents' behavior and improve network performance. In this article, we review some recent developments in pinning control. Stability algorithms and pining strategies in different types of complex networks are presented and compared. Adaptive pinning control is also summarized. In addition, the research extended to discrete-time case is reviewed. As some related research, the development in consensus and flocking of multi-agent system are introduced briefly. At last, we give some ideas about pinning control in social networks. © 2012 Huazhong Univ of Sci & Tec.

关键词： Complex networks

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Generative Adversarial Network-Based Electromagnetic Signal Classification: A Semi- Supervised Learning Framework

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China Communications 2020年第10期17卷 157-169页

作者： Huaji Zhou Licheng Jiao Shilian Zheng Lifeng Yang Weiguo Shen Xiaoniu Yang Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education School of Artificial IntelligenceXidian UniversityXi'an 710071China Science and Technology on Communication Information Security Control Laboratory Jiaxing 314033China

Generative adversarial network(GAN)has achieved great success in many fields such as computer vision,speech processing,and natural language processing,because of its powerful capabilities for generating realistic *** this paper,we introduce GAN into the field of electromagnetic signal classification(ESC).ESC plays an important role in both military and civilian ***,in many specific scenarios,we can’t obtain enough labeled data,which cause failure of deep learning methods because they are easy to fall into ***,semi-supervised learning(SSL)can leverage the large amount of unlabeled data to enhance the classification performance of classifiers,especially in scenarios with limited amount of labeled *** present an SSL framework by incorporating GAN,which can directly process the raw in-phase and quadrature(IQ)signal *** to the characteristics of the electromagnetic signal,we propose a weighted loss function,leading to an effective classifier to realize the end-to-end classification of the electromagnetic *** validate the proposed method on both public RML2016.04c dataset and real-world Aircraft Communications Addressing and Reporting System(ACARS)signal *** experimental results show that the proposed framework obtains a significant increase in classification accuracy compared with the state-of-the-art studies.

关键词： generative adversarial network semi-supervised learning electromagnetic signal classification end-to-end classification weighted loss function

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Tracking control of pneumatic muscle using Lyapunov based control method

Tracking control of pneumatic muscle using Lyapunov based co...

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2012 International Conference on Modelling, Identification and control, ICMIC 2012

作者： Elobaid, Youssif M. T. Huang, Jian Wang, Yongji Wu, Jun Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780956715715

Presently pneumatic muscles (PMs) are used in various applications due to their simple construction, lightweight and high force to weight ratio. However, pneumatic muscles are facing various problems due to their nonlinear characteristic in various mechanical applications. The model of PM is nonlinear and time-varying. In this paper, a Lyapunov-based control (LBC) approach is proposed for the control of PM. Based on the nonlinear characteristic of PM, a dynamic model of the PM actuator with pulling a mass against gravity is formed. control objectives are both a regulation and an asymptotic tracking of a desired trajectory. Stability analysis based on Lyapunov method with respect to our proposed control law is discussed. The simulation results show the validity, effectiveness and enhancing robustness of the proposed method. © 2012 Huazhong Univ of Sci & Tec.

关键词： Lyapunov methods

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