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Model-Independent Robust Consensus for Multiple Euler-Lagrange Systems of an Uncertain Leader

IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年第12期54卷 7279-7290页

作者： Long, Mingkang Su, Housheng Huazhong Univ Sci & Technol Educ Minist China Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

In this article, we introduce adaptive robust observers for the estimation of comprehensive state variables and model parameters of a leader system. In particular, we suppose that the communication network among followers suffers communication link faults (CLFs), and the leader contains uncertainty, which means no follower knows the model parameters of leader system. Then, by applying the proposed observers, we elaborate on the design of a robust model-independent controller tailored for the leader-follower consensus problem (LFCP) of multiple Euler-Lagrange systems (MELSs). In contrast to the controllers currently employed for the LFCP in MELSs, the controller developed herein exhibits robustness against bounded external disturbances. Besides, the controller does not rely on the specific structure or characteristics of the Euler-Lagrange (EL) system model. At last, we provide simulation examples to demonstrate the validity of the proposed observers and the robust controller in the context of the LFCP for MELSs.

关键词： Observers Adaptation models Vectors Adaptive systems Communication networks Robustness Eigenvalues and eigenfunctions Communication link faults (CLFs) leader-follower consensus problem (LFCP) model-independent multiple Euler-Lagrange systems (MELSs) robust control uncertain leader

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A quick scale-invariant interest point detecting approach

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MACHINE VISION AND APPLICATIONS 2010年第3期21卷 351-364页

作者： Gao, Jian Huang, Xinhan Liu, Bo HUST Dept CSE Minist Educ Image Proc & Intelligent Control Key Lab Wuhan 430074 Peoples R China BFSU Beijing 100089 Peoples R China

To improve the real-time performance, a quick scale-invariant interest point detecting approach based on the image color information is proposed in this paper. The approach uses the scale normalized Laplacian operator to extract the interest points in the incomplete image pyramid. A new local descriptor is presented in the approach to compute the feature vector of each interest point. The descriptor is made up with several subregions like the SIFT (Scale-Invariant Feature Transform) descriptor, meanwhile, it chooses the mean values of different color components in each subregion as the feature vector's elements to differentiate color objects better and reduce the descriptor's dimension. Through the experiment, the detected interest points are robust to many image transformations and the approach is indicative of needing less computation than other interest point detecting algorithms. The research discloses that the approach can obtain both superior stability and real-time performance at the same time.

关键词： Computer vision Feature detection Feature matching Color information Real-time performance

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EEG-Based Driver Drowsiness Estimation Using Feature Weighted Episodic Training

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IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING 2019年第11期27卷 2263-2273页

作者： Cui, Yuqi Xu, Yifan Wu, Dongrui Huazhong Univ Sci & Technol Minist Educ Image Proc & Intelligent Control Sch Artificial Intelligence & Automat Key Lab Wuhan 430074 Hubei Peoples R China

Drowsy driving is pervasive, and also a major cause of traffic accidents. Estimating a driver's drowsiness level by monitoring the electroencephalogram (EEG) signal and taking preventative actions accordingly may improve driving safety. However, individual differences among different drivers make this task very challenging. A calibration session is usually required to collect some subject-specific data and tune the model parameters before applying it to a new subject, which is very inconvenient and not user-friendly. Many approaches have been proposed to reduce the calibration effort, but few can completely eliminate it. This paper proposes a novel approach, feature weighted episodic training (FWET), to completely eliminate the calibration requirement. It integrates two techniques: feature weighting to learn the importance of different features, and episodic training for domain generalization. Experiments on EEG-based driver drowsiness estimation demonstrated that both feature weighting and episodic training are effective, and their integration can further improve the generalization performance. FWET does not need any labelled or unlabelled calibration data from the new subject, and hence could be very useful in plug-and-play brain-computer interfaces.

关键词： Drowsy driving domain generalization EEG episodic training feature weighting

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Enhanced multi-level filter algorithm and its VLSI architecture

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INTERNATIONAL JOURNAL OF ELECTRONICS 2007年第2期94卷 157-169页

作者： Zhaoqing, Z. Chaoyang, C. Jianwei, S. Liqiang, J. Tianxu, Z. Huazhong Univ Sci & Technol Inst Pattern Recognit & Artificial Intelligence State Key Lab Image Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

This paper presents an enhanced multi-level filter algorithm and its Very Large Scale Integration (VLSI) architecture for infrared image processing. The modified multi-level filter algorithm resolves the splitting targets problem using Gaussian pyramid processing. Owning three filtering paths, the proposed VLSI architecture of the filter can simultaneously enhance small targets with different sizes in infrared images. Some design techniques in implementing hardwired multiplication, subsample and asynchronous FIFO have been presented. This VLSI architecture has been implemented using Semiconductor Manufacturing International Corporation (SMIC) 0.35 mu m 4-layer CMOS technology. The simulation results show that it not only effectively suppresses background, eliminates noise and enhances small targets in an infrared image comparing with other small target detective methods, but also meets infrared image real-time processing requirements (5M similar to 10M pixels/s). The implemented filter chip consists of 60,284 gates and 8 K Static Random Access Memory (SRAM), operates at 50 MHz.

关键词： VLSI infrared image processing filters

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On 8mm microwave radiometric imaging system

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INTERNATIONAL JOURNAL OF INFRARED AND MILLIMETER WAVES 1999年第6期20卷 1129-1135页

作者： Guo, W Li, FT Zhang, ZY Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ China Inst AI & Pattern Recognit Wuhan 430074 Peoples R China

This paper describes structure of imaging system, imaging mechanism of microwave radiometer, and the microwave radiation image features and recognition. Results of image experiments show: on microwave radiation image,... 详细信息

关键词： microwave radiation characteristic sampling imaging system

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Hierarchical Flow Model-Based Impact Assessment of Cyberattacks for Critical Infrastructures

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IEEE SYSTEMS JOURNAL 2019年第4期13卷 3944-3955页

作者： Zhu, Qianxiang Qin, Yuanqing Zhou, Chunjie Fei, Li Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Sch Artificial Intelligence & Automat Wuhan 430074 Hubei Peoples R China

Critical infrastructures (CIs) are essential for the national security, economy, and public safety, whose protection against cyberattacks has become the focus of significant attention. Impact assessment plays an important role in this protection, which provides real-time situations for security managers. The assessment of CIs not only need to analyze the cyberattack's impact on any specific station, but also to consider the spreading process of the negative impact. However, few research in this domain consider the above two aspects simultaneously due to the complexity of CIs and their operation. To tackle this problem, a hierarchical flow model (HFM)-based impact assessment is presented. In this approach, a novel HFM method is proposed to describe a system from a function system perspective, which combines a flow model and hierarchical knowledge. By using this method, a CI model which considers cyber-physical interaction within a station, dependence among stations, and the topological structure of the physical network is established. Next, based on the CI model, an impact assessment is proposed to quantify the loss which is caused by the impact spreading within the CI network. Finally, case studies on a gas supply system are conducted to verify the effectiveness of the proposed approach.

关键词： Critical infrastructures cybersecurity protection hierarchical flow model impact assessment system of systems

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Semiglobal Observer-Based Non-Negative Edge Consensus of Networked Systems With Actuator Saturation

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IEEE TRANSACTIONS ON CYBERNETICS 2020年第6期50卷 2827-2836页

作者： Su, Housheng Sun, Yaping Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China

The observer-based edge-consensus problem of networked continuous-time dynamical systems with edge state non-negative constraint and actuator saturation is considered in this paper. Based on line graph theory, low-gain output-feedback technique and algebraic Riccati equation (ARE)-based method, two edge-consensus algorithms are designed to achieve the observer-based edge consensus, in which the specific mathematical expressions of the two algorithms are obtained. Meanwhile, sufficient conditions are obtained to meet the bounded inputs and the non-negative edge states by combining with the ARE-based low-gain output-feedback technique and the positive system theory. Moreover, the feedback-gain and observer-gain matrices which must meet the sufficient conditions at the same time are existed and easy to obtain. Finally, two simulation cases are introduced to show the effectiveness of the theoretical results.

关键词： Actuators Network topology Observers Kinetic theory Heuristic algorithms Graph theory Cybernetics Actuator saturation edge consensus low-gain output feedback non-negative constraint observer

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A new fault diagnosis method for cold test based on frequency analysis

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND control 2013年第2期18卷 146-157页

作者： Wei, Li Kun, Zhang Xi, Chen Huazhong Univ Sci & Technol Dept Control Sci & Engn Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Hubei Peoples R China

An effective model for diesel engine in cold test has been developed in this paper. The mathematical model of diesel engine is mainly composed by four parts: turbocompressor model, intake manifold model, exhaust manifold model and the pressure model of cylinder in cold test. And then a new engine faults diagnosis method based on frequency domain analysis is presented. The typical faults of diesel engine in cold test, including the cylinder work phase fault and intake/exhaust valve phase fault, are distinguished by the amplitude frequency performance of engine torque. And the location of the engine faults is solved by the performance of the phases of low-frequency of engine torque signals. It has been proved to be an effective method to identify and locate the faults of the diesel engine in cold test.

关键词： cold test fault simulation frequency analysis engine modelling fault diagnosis

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A small universal spiking neural P system with communication on request

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NEUROCOMPUTING 2018年 275卷 1622-1628页

作者： Pan, Tong Shi, Xiaolong Zhang, Zheng Xu, Fei Huazhong Univ Sci & Technol Sch Automat Educ Minist China Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Hubei Peoples R China

Spiking neural P systems (SN P systems, for short) are known as a class of distributed parallel computing models, which are inspired by the way in which neurons process and communicate information with each other by means of spikes. In this work, we focus on a new variant of SN P systems, namely spiking neural P systems with communication on request (SNQ P systems, for short). We concentrate on searching for a small universal SNQ P system. The best known result is that 49 neurons are enough for constructing a Turing universal SNQ P system. Here, we construct a Turing universal SNQ P system with only 14 neurons, which answers an open problem whether the number of neurons for constructing a Turing universal SNQ P system can be further improved. (c) 2017 Elsevier B.V. All rights reserved.

关键词： Bio-inspired computing Membrane computing Spiking neural P system Register machine Universality

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Recovering unknown topology in a two-layer multiplex network:One layer infers the other layer

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Science China(Technological Sciences) 2022年第7期65卷 1493-1505页

作者： LIU Hui SHANG ZhiCheng REN ZiYi LI Yan ZENG ZhiGang LU JunAn School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China School of Mathematics and Statistics Wuhan UniversityWuhan 430072China

There have been increasing interests in studying multiplex dynamical networks *** paper focuses on topology identiflcation of two-layer multiplex networks with peer-to-peer interlayer *** a two-layer network model in which different layers have different coupling patterns,we propose novel methods to recover unknown topological structure of one layer,using the information of the other layer known as a *** proposed methods make full use of the measured evolutional states of the multiplex network itself,and treat the layer with a known structure as an auxiliary layer which is designed to identify the unknown topological *** with the traditional synchronization-based identiflcation method,the proposed methods are in no need of constructing an additional auxiliary network to identify the unknown topological layer,and thus greatly reduce the cost of topology ***,numerical simulations validate the effectiveness of the proposed methods.

关键词： multiplex network synchronization topology identiflcation

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