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Mixed H_(∞)/Passive Exponential Synchronization for Delayed Memristive Neural Networks with Switching Event-Triggered Control

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Journal of Systems Science & Complexity 2024年第1期37卷 294-317页

作者： WU Wenhuang GUO Lulu CHEN Hong Shanghai research Institute for Intelligent Autonomous Systems Tongji UniversityShanghai 200092China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

This paper is devoted to event-triggered synchronization of delayed memristive neural networks with H∞and passivity performance.The aim is to guarantee the exponential synchronization and mixed H∞and passivity control for memristive neural networks by using event-triggered control.Firstly,a switching system is constructed under the event-triggered control strategy.Then,by adopting a piece-wise Lyapunov functional,a sufficient condition is established for the exponential synchronization and mixed H_(∞)and passivity performance.Moreover,an event-triggered controller design scheme is proposed using matrix decoupling method.Finally,the effectiveness of the designed controller is exemplified by a numerical example.

关键词： Event-triggered control exponential synchronization memristive neural networks time delays.

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Insulation Design Rule for a Spacer in SF_(6)/N_(2)-filled DC Gas Insulated Apparatus

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CSEE Journal of Power and Energy Systems 2024年第2期10卷 727-735页

作者： Hongyang Zhou Guoming Ma Meng Zhang Cong Wang Youping Tu Chengrong Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources and the Beijing Key Laboratory of High Voltage and EMC North China Electric Power UniversityBeijing 102206China

A recurring challenge of a DC SF_(6)/N_(2)-filled GIS/GIL apparatus is the charge accumulation at DC stress.The conventional design rules and knowledge of AC spacers may not be applicable for this new type of apparatus.A novel design rule is proposed considering the effect of accumulated charge on the threshold of electric field strength being resistant to the superposed voltage.A surface charge accumulation simulation model is introduced,and the key parameters in the simulation model are measured.In addition,an experimental platform for a 100 kV spacer flashover test is established.Spacer flashover tests under superimposed voltage with opposing polarities are carried out,and the withstanding voltage of the spacer is obtained.Finally,based on the proposed model,the threshold of the surface electric field strength(tangential component)on the DC spacer in SF_(6)/N_(2) mixed gases is discussed.For a reliable insulation design of a DC GIS/GIL apparatus filled with 0.7 MPa SF_(6)/N_(2),the threshold of surface electric field strength on the DC spacer is 12 kV/mm.The insulation design rule can be referenced in the design of a high-voltage DC SF_(6)/N_(2)-filled GIS/GIL apparatus.

关键词： Charge accumulation DC spacer flashover voltage SF_(6)/N_(2) threshold of surface electric field strength

Electricity Pricing with Continuous-time Commodity Model and Non-monotonic Load Curve

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CSEE Journal of Power and Energy Systems 2024年第1期10卷 272-280页

作者： Lijia Han Yue Li Haoyong Chen Ningning Lu Mathematical and Physical Science School North China Electric Power UniversityBeijing 102206China School of Electric Power Engineering South China University of TechnologyGuangzhou 510641China

Under the "carbon peak and carbon neutrality"background,clean energy enters the market on a large scale,so it is very important to study the pricing theory of electricity.The bright spot of this paper is that the load curve is more practical.In the original version of electricity pricing theory based on continuous time commodity model,the load curve is supposed to be a monotonic function with time for simplicity of derivation,which is not realistic.To overcome this defect,load curves are supposed to be in shapes of a unimodal model and multimodal cases in this paper,which are more in conformity with the actual load curve in real-world power markets.Two study cases are used to demonstrate the rationality of the proposed models.These results together with the authors'previous work provide a complete pricing scheme for continuous-time electricity commodity model.

关键词： Functional optimization market equilibrium spot pricing variational method

SNR-adaptive deep joint source-channel coding scheme for image semantic transmission with convolutional block attention module

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The Journal of china universities of Posts and Telecommunications 2024年第1期31卷 1-11页

作者： Yang Yujia Liu Yiming Zhang Wenjia Zhang Zhi State Key Laboratory of Networking and Switch Technology Beijing University of Posts and TelecommunicationsBeijing 100876China

With the development of deep learning(DL),joint source-channel coding(JSCC)solutions for end-to-end transmission have gained a lot of attention.Adaptive deep JSCC schemes support dynamically adjusting the rate according to different channel conditions during transmission,enhancing robustness in dynamic wireless environment.However,most of the existing adaptive JSCC schemes only consider different channel conditions,ignoring the different feature importance in the image processing and transmission.The uniform compression of different features in the image may result in the compromise of critical image details,particularly in low signal-to-noise ratio(SNR)scenarios.To address the above issues,in this paper,a dual attention mechanism is introduced and an SNR-adaptive deep JSCC mechanism with a convolutional block attention module(CBAM)is proposed,in which matrix operations are applied to features in spatial and channel dimensions respectively.The proposed solution concatenates the pooling feature with the SNR level and passes it sequentially through the channel attention network and spatial attention network to obtain the importance evaluation result.Experiments show that the proposed solution outperforms other baseline schemes in terms of peak SNR(PSNR)and structural similarity(SSIM),particularly in low SNR scenarios or when dealing with complex image content.

关键词： semantic communication joint source-channel coding image transmission

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Prescribed time control based on the periodic delayed sliding mode surface without singularities

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Science china(Information Sciences) 2024年第7期67卷 256-270页

作者： Bin ZHOU Yi DING Kang-Kang ZHANG Guang-Ren DUAN Center for Control Theory and Guidance Technology Harbin Institute of Technology

In this paper, nonsingular prescribed-time control is studied based on periodic delayed sliding mode surfaces. Different from the existing sliding mode control, where either singularity problems may appear or the convergence time depends on the initial state, the proposed sliding mode control approaches can achieve prescribed-time convergence without singularity. The proposed nonsingular sliding mode control approaches can be applied to both second-order and high-order nonlinear systems with prescribed-time convergence. As applications of the proposed sliding mode control approaches, the control of hypersonic vehicle systems is revisited. Numerical simulations on the nonlinear model of the hypersonic vehicle system show the effectiveness of the proposed methods.

关键词： prescribed-time control smooth periodic delayed feedback sliding mode control high-order nonlinear systems hypersonic vehicle systems

Optimizing Optical Fiber Faults Detection:A Comparative Analysis of Advanced Machine Learning Approaches

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Computers, Materials & Continua 2024年第5期79卷 2697-2721页

作者： Kamlesh Kumar Soothar Yuanxiang Chen Arif Hussain Magsi Cong Hu Hussain Shah School of Electronics Engineering Beijing University of Posts and TelecommunicationsBeijing100876China State Key Laboratory of Integrated Services Networks Xidian UniversityXi’an710071China State Key Laboratory ofNetworking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing100876China

Efficient optical network management poses significant importance in backhaul and access network communicationfor preventing service disruptions and ensuring Quality of Service(QoS)satisfaction.The emerging faultsin optical networks introduce challenges that can jeopardize the network with a variety of faults.The existingliterature witnessed various partial or inadequate solutions.On the other hand,Machine Learning(ML)hasrevolutionized as a promising technique for fault detection and prevention.Unlike traditional fault managementsystems,this research has three-fold contributions.First,this research leverages the ML and Deep Learning(DL)multi-classification system and evaluates their accuracy in detecting six distinct fault types,including fiber cut,fibereavesdropping,splicing,bad connector,bending,and PC connector.Secondly,this paper assesses the classificationdelay of each classification algorithm.Finally,this work proposes a fiber optics fault prevention algorithm thatdetermines to mitigate the faults accordingly.This work utilized a publicly available fiber optics dataset namedOTDR_Data and applied different ML classifiers,such as Gaussian Naive Bayes(GNB),Logistic Regression(LR),Support Vector Machine(SVM),K-Nearest Neighbor(KNN),Random Forest(RF),and Decision Tree(DT).Moreover,Ensemble Learning(EL)techniques are applied to evaluate the accuracy of various classifiers.In addition,this work evaluated the performance of DL-based Convolutional Neural Network and Long-Short Term Memory(CNN-LSTM)hybrid classifier.The findings reveal that the CNN-LSTM hybrid technique achieved the highestaccuracy of 99%with a delay of 360 s.On the other hand,EL techniques improved the accuracy in detecting fiberoptic faults.Thus,this research comprehensively assesses accuracy and delay metrics for various classifiers andproposes the most efficient attack detection system in fiber optics.

关键词： Fiber optics fault detection multiclassification machine learning ensemble learning

Unleashing potentials with deep learning: decoding the complex events for distributed fiber optic sensing applications

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Science china(Information Sciences) 2024年第5期67卷 337-338页

作者： Yujiao LI Liqin HU Kuanglu YU Institute of Information Science School of Computer and Information Technology Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing Jiaotong University

After decades of research, distributed fiber optic sensors have become essential tools for precise long-distance measurements. They are applied across various sectors such as railway transportation, gas and petroleum, and smart grids. Signal processing, particularly in phase-sensitive optical time domain reflectometry(Φ-OTDR) event recognition and classification, is a primary research focus.

关键词： Deep learning

Tailoring electron vortex beams with customizable intensity patterns by electron diffraction holography

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Opto-Electronic Advances 2024年第2期7卷 14-21页

作者： Pengcheng Huo Ruixuan Yu Mingze Liu Hui Zhang Yan-qing Lu Ting Xu National Laboratory of Solid-State Microstructures and Collaborative Innovation Center of Advanced Microstructures Nanjing UniversityNanjing 210093China College of Engineering and Applied Sciences Key Laboratory of Intelligent Optical Sensing and Manipulation and Jiangsu Key Laboratory of Artificial Functional MaterialsNanjing UniversityNanjing 210093China

An electron vortex beam(EVB) carrying orbital angular momentum(OAM) plays a key role in a series of fundamental scientific researches, such as chiral energy-loss spectroscopy and magnetic dichroism spectroscopy. So far, almost all the experimentally created EVBs manifest isotropic doughnut intensity patterns. Here, based on the correlation between local divergence angle of electron beam and phase gradient along azimuthal direction, we show that free electrons can be tailored to EVBs with customizable intensity patterns independent of the carried OAM. As proof-of-concept, by using computer generated hologram and designing phase masks to shape the incident free electrons in the transmission electron microscope, three structured EVBs carrying identical OAM are tailored to exhibit completely different intensity patterns. Furthermore, through the modal decomposition, we quantitatively investigate their OAM spectral distributions and reveal that structured EVBs present a superposition of a series of different eigenstates induced by the locally varied geometries. These results not only generalize the concept of EVB, but also demonstrate an extra highly controllable degree of freedom for electron beam manipulation in addition to OAM.

关键词： electron vortex beam orbital angular momentum diffraction holography

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Two-layer Lagrange-based relay network topology and trajectory design for solar system explorations

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Science china(Information Sciences) 2024年第6期67卷 342-358页

作者： Jun CAO Jian JIAO Hao LIU Rongxing LU Qinyu ZHANG Guangdong Provincial Key Laboratory of Aerospace Communication and Networking Technology Harbin Institute of Technology (Shenzhen) Faculty of Computer Science (FCS) University of New Brunswick

Exploration targeting outer planets and even the edge of the solar system is an emerging direction for the deep-space exploration in the next decades. To address this challenge, a novel two-layer Lagrangebased relay network topology is proposed in this study. Specifically, we utilize the Sun-Mars and Sun-Saturn Lagrange points(LPs) L4 and L5 to build a two-layer backbone relay network, which ensures continuous and high-efficiency communication capability for the exploration of the solar system. Furthermore, we utilize the planetary gravity assist and design the transfer trajectory of backbone relays with the help of planetary celestial body motion equations and Kepler's laws. Moreover, we conduct link budget analysis for multihop relay transmission under Gamma-Gamma distribution, shadowed Rician fading, and additive white Gaussian noise channels in several typical exploration scenarios and validate that the LP relays can effectively support future deep-space exploration missions.

关键词： deep-space communication Lagrangian points backbone relay network transfer trajectory relay selection