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Exponential Stability of Impulsive system via Saturated Sliding Mode Control

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 469-471页

作者： Miaomiao Yu Xiaodi Li the Shandong Provincial engineering research center of system Control and intelligent Technology Shandong Normal University School of Mathematics and Statistics Shandong Normal University IEEE

Dear Editor,This letter presents a class of saturated sliding mode control (SMC)strategy for linear systems subject to impulsive disturbance and input saturation. To ensure the feasibility of proposed SMC under saturation, a relationship is established among attraction domain, saturation structure and control gain.

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Fractal autoencoder with redundancy regularization for unsupervised feature selection

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Science China(Information Sciences) 2025年第2期68卷 89-102页

作者： Meiting SUN Fangyu LI Honggui HAN School of Information Science and Technology Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and intelligent system engineering research center of Digital Community Ministry of Education Beijing Institute of Artificial Intelligence

Feature selection is a crucial step in data preprocessing because feature selection reduces the dimensionality of data by eliminating irrelevant and redundant features. Since manual labeling is expensive, unsupervised feature selection has received increasing attention in recent years. However, existing unsupervised feature selection methods tend to prioritize selecting highly correlated features over exploring feature diversity. Thus, a regularized fractal autoencoder(RFAE) method is proposed to select informative features in an unsupervised way. Specifically, the fractal autoencoder network extends autoencoders to construct a correspondence neural network and a selection neural network. The correspondence neural network exploits interfeature correlations and the selection neural network selects the informative features. A redundancy regularization strategy consists of a redundancy elimination regularization term based on the dependency between features and a sparse regularization term based on the group lasso. The redundancy regularization strategy eliminates feature subset redundancy and enhances network generalization ability. Extensive experimental results on six publicly available datasets show that the proposed RFAE outperforms the compared methods regarding clustering accuracy and classification accuracy. Moreover, the proposed RFAE achieves acceptable computation efficiency.

关键词： unsupervised feature selection fractal autoencoder correspondence neural network selection neural network redundancy regularization strategy

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Time-Varying Formation Tracking Control of Heterogeneous Multi-Agent systems With Intermittent Communications and Directed Switching Networks

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 294-296页

作者： Yuhan Wang Zhuping Wang Hao Zhang Huaicheng Yan the Shanghai research Institute for intelligent Autonomous systems Tongji University the National Key Laboratory of Autonomous intelligent Unmanned systems the Frontiers Science center for intelligent Autonomous system of Ministry of Education the College of Electronic and Information engineering the Department of Control Science and Engineering Tongji University the Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education the School of Information Science and engineering East China University of Science and Technology

Dear Editor,This letter is concerned with the problem of time-varying formation tracking for heterogeneous multi-agent systems(MASs) under directed switching networks. For this purpose, our first step is to present so... 详细信息

关键词： Switches Topology Observers Formation control Event detection Switched systems Multi-agent systems Control theory Autonomous systems Stability

research on the balance optimization algorithm of image recognition accuracy and speed based on autocollimator measurement

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Optoelectronics Letters 2025年第2期21卷 121-128页

作者： LI Renpu MA Long CUI Jiwen GUO Junqi Andrei KULIKOV WEN Dandan Chongqing engineering research center of intelligent sensing Technology and Microsystem Chongqing University of Post and TelecommunicationsChongqing 400065China School of Instrumentation Science and engineering Harbin Institute of TechnologyHarbin 150080China Higher School of engineering and Technology ITMO UniversitySaint Petersburg 197101Russia

The autocollimator is an important device for achieving precise,small-angle,non-contact *** primarily obtains angular parameters of a plane target mirror indirectly by detecting the position of the imaging *** is limited report on the core algorithmic techniques in current commercial products and recent scientific *** paper addresses the performance requirements of coordinate reading accuracy and operational speed in autocollimator image *** proposes a cross-image center recognition scheme based on the Hough transform and another based on Zernike moments and the least squares *** experimental evaluation of the accuracy and speed of both schemes,the optimal image recognition scheme balancing measurement accuracy and speed for the autocollimator is *** these,the center recognition method based on Zernike moments and the least squares method offers higher measurement accuracy and stability,while the Hough transform-based method provides faster measurement speed.

关键词： image optimization recognition

A Multifunctional Hydrogel with Multimodal Self-Powered sensing Capability and Stable Direct Current Output for Outdoor Plant Monitoring systems

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Nano-Micro Letters 2025年第4期17卷 1-24页

作者： Xinge Guo Luwei Wang Zhenyang Jin Chengkuo Lee Department of Electrical&Computer engineering National University of Singapore4 Engineering Drive 3Singapore 117576Singapore center for intelligent Sensors and MEMS(CISM) National University of Singapore5 Engineering Drive 1Singapore 117608Singapore NUS Graduate School-Integrative Sciences and engineering Program(ISEP) National University of SingaporeSingapore 119077Singapore research center for Sustainable Urban Farming(SUrF) National University of SingaporeSingapore 117558Singapore

Smart farming with outdoor monitoring systems is critical to address food shortages and sustainability *** systems facilitate informed decisions that enhance efficiency in broader environmental *** outdoor systems equipped with energy harvesters and self-powered sensors often struggle with fluctuating energy sources,low durability under harsh conditions,non-transparent or non-biocompatible materials,and complex ***,a multifunctional hydrogel is developed,which can fulfill all the above requirements and build selfsustainable outdoor monitoring systems solely by *** can serve as a stable energy harvester that continuously generates direct current output with an average power density of 1.9 W m^(-3)for nearly 60 days of operation in normal environments(24℃,60%RH),with an energy density of around 1.36×10^(7)J m^(-3).It also shows good self-recoverability in severe environments(45℃,30%RH)in nearly 40 days of continuous ***,this hydrogel enables noninvasive and self-powered monitoring of leaf relative water content,providing critical data on evaluating plant health,previously obtainable only through invasive or high-power consumption *** potential extends to acting as other self-powered environmental *** multifunctional hydrogel enables self-sustainable outdoor systems with scalable and low-cost production,paving the way for future agriculture.

关键词： Self-powered sensor Hydrogel Energy harvester Outdoor farming Self-sustainable IoT

NASTCNN: a spatio-temporal convolutional neural network with non-local attention mechanism for image-induced brain activity pattern recognition

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Optoelectronics Letters 2025年

作者： TAN Xiangxin SHAO Mingxiong ZENG Ke GU Yue School of Computer Science and engineering， Tianjin University of Technology engineering research center of Learning-Based intelligent system (Ministry of Education)， Tianjin University of Technology Krembil research Institute， University Health Network

Deciphering the brain’s visual processing mechanisms has always been a hot topic. Using neural signal patterns to predict the corresponding external visual stimuli is crucial in understanding the interaction of real visual scenes. There are some challenges in the study of image-induced brain activity pattern recognition based on electroencephalogram (EEG)， e.g. how to fully utilize the effective features of EEG signals to improve the classification， and how the frequency and the length of EEG effect the model performance. We design an experimental paradigm that minimizes the interaction between visual stimuli， and propose a spatio-temporal convolutional neural network with non-local attention mechanism (NASTCNN) for image-induced brain activity pattern recognition. The framework utilizes non-local feature extraction operations to realize global information interaction between EEG signals over long distances and enhance the feature expression of some important information. Our model achieves the best performance on both MNIST-EEG and ImageNet-EEG datasets. The classification results are 24.00% and 50.10% respectively， higher than the random probability. We also analyze the effects of different EEG frequency bands and time subsequences of different lengths on the classification performance and which brain regions are activated over time. The results show that when full frequency band and entire length sequence are selected， the classification result is optimal. The occipital region is essential for processing visual tasks， and the temporal region and some frontal regions also play important role in the later stage of visual decoding. This research can help us better understand the visual processing mechanism of the brain.

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Spatiotemporal deformation analysis of glaciers and surrounding landscapes in the Shishapangma region using InSAR techniques

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Journal of Mountain Science 2025年第1期22卷 210-229页

作者： LIANG Wenli LIU Rui JI Qin KOU Pinglang Chongqing Key Laboratory of GIS Application School of Geography and TourismChongqing Normal UniversityChongqing 401331China National Earth system Science Data center Beijing 100000China Chongqing engineering research center of Spatial Big Data intelligent Technology Chongqing University of Posts and TelecommunicationsChongqing 400065China Key Laboratory of Tourism Multisource Data Perception and Decision Ministry of Culture and Tourism(TMDPDMCT)Chongqing University of Posts and TelecommunicationsChongqing 400065China

Glacier dynamics in the Himalayan midlatitudes,particularly in regions like the Shishapangma,are not yet fully understood,especially the localized topographic and climatic impacts on glacier *** study analyzes the spatiotemporal characteristics of glacier surface deformation in the Shishapangma region using the Small Baseline Subset(SBAS)Interferometric Synthetic Aperture Radar(In SAR)*** analysis reveals an average deformation rate of-4.02±17.65 mm/yr across the entire study area,with glacier regions exhibiting significantly higher rates of uplift(16.87±13.20 mm/yr)and subsidence(20.11±14.55 mm/yr)compared to non-glacier *** identifies significant surface lowering on the mountain flanks and localized uplift in certain catchments,emphasizing the higher deformation rates in glacial areas compared to non-glacial *** found a strong positive correlation between temperature and cumulative deformation(correlation coefficient of 0.63),particularly in glacier areas(0.82).The research highlights the role of temperature as the primary driver of glacier wastage,particularly at lower elevations,with strong correlations found between temperature and cumulative *** also indicates the complex interactions between topographic features,notably,slope gradient,which shows a positive correlation with subsidence rates,especially for slopes below 35°.South-,southwest-,and west-facing slopes exhibit significant uplift,while north-,northeast-,and east-facing slopes predominantly ***,we identified transition zones between debris-covered glaciers and clean ice as areas of most intense deformation,with average rates exceeding 30 mm/yr,highlighting these as potential high-risk zones for *** study comprehensively analyzes the deformation characteristics in both glacier and non-glacier areas in the Shishapangma region,revealing the complex interplay of topographic,climatic,and hydrological factors influencing glacier dynamic

关键词： Glacier melting SBAS-InSAR Topographic factors Temperature change Middle Himalayas

Learning to see speckle in the weak laser field through multimode fiber

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Optoelectronics Letters 2025年

作者： JI Yunqi SONG Binbin LI Xueqing LI Yonghui The engineering research center of Learning-Based intelligent system (Ministry of Education)， the Key Laboratory of Computer Vision and systems (Ministry of Education)， and the School of Computer Science and engineering， Tianjin University of Technology

Multimode fibers (MMFs) have great potential for endoscopic imaging due to the high number of modes and a small core diameter. Deep learning based on neural networks has received increasing attention in the field of scattering image reconstruction. However， most studies focus on designing complex network architectures to improve reconstruction， but these network models struggle to reconstruct images in a weak laser field. In the paper， a lightweight generative adversarial network model combined with a histogram specification algorithm is designed to reconstruct speckles in the weak laser field through MMF. Experimental results show that the reconstruction results of our algorithm have better metrics. Moreover， the model demonstrates excellent cross-domain generalization ability with regards to the Fashion-MNIST dataset. It is worth mentioning that we found that the speckles after inactivation still retain the ability to be reconstructed， which enhances the robustness of the model

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Broadband low-frequency sound absorption of multifunctional composite metastructure

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Science China(Technological Sciences) 2025年第2期68卷 114-124页

作者： Yilong YANG Shanshan LIU Yan LI Tong GAO Yongdong PAN Yong LI Yabin JIN School of Aerospace engineering and Applied Mechanics Tongji UniversityShanghai 200092China State International Joint research center of Aerospace Design and Additive Manufacturing Northwestern Polytechnical UniversityXi’an 710072China Institute of Acoustics School of Physics Science and EngineeringTongji UniversityShanghai 200092China Shanghai Key Laboratory of intelligent sensing and Detection Technology School of Mechanical and Power EngineeringEast China University of Science and TechnologyShanghai 200237China Shanghai Institute of Aircraft Mechanics and Control Shanghai 200092China

In this study,we fabricated multifunctional metastructures from carbon fiber-reinforced plastic composites using additive manufacturing *** metastructures are characterized by their lightweight,load-bearing capacity,and broadband low-frequency sound absorption *** metastructure consists of 36 unit cells,and non-local coupling mechanism was considered for designing the sound absorption *** developed an acoustic impedance theory tailored for the metastructure,facilitating an analysis of thermal and viscous dissipation *** is proven theoretically and experimentally that the proposed composite metastructure can achieve a noise reduction with an average sound absorption coefficient greater than 0.9 across frequencies in the rage of 330-1500 *** also studied the metastructure’s quasi-static and cyclic compression performance,confirming its efficient absorption capabilities after cyclic *** proposed design and additive manufacturing method for composite metastructures provides a novel pathway for creating lightweight,multifunctional structures with diverse applications,such as aerospace engineering.

关键词： composite metastructure broadband sound absorption additive manufacturing

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