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arXiv 2025年

作者： Yang, Song Fu, Haotian Zhang, Herui Zhang, Peng Li, Wei Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China Department of Biomedical Engineering College of Life Science and Technology Huazhong University of Science and Technology Wuhan430074 China

Decoding brain signals accurately and efficiently is crucial for intra-cortical brain-computer interfaces. Traditional decoding approaches based on neural activity vector features suffer from low accuracy, whereas deep learning based approaches have high computational cost. To improve both the decoding accuracy and efficiency, this paper proposes a spiking neural network (SNN) for effective and energy-efficient intra-cortical brain signal decoding. We also propose a feature fusion approach, which integrates the manually extracted neural activity vector features with those extracted by a deep neural network, to further improve the decoding accuracy. Experiments in decoding motor-related intra-cortical brain signals of two rhesus macaques demonstrated that our SNN model achieved higher accuracy than traditional artificial neural networks;more importantly, it was tens or hundreds of times more efficient. The SNN model is very suitable for high precision and low power applications like intracortical brain-computer interfaces. © 2025, CC BY.

关键词： Deep neural networks

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Robot Visual Sliding Mode Servoing using SIFT Features 35

Robot Visual Sliding Mode Servoing using SIFT Features

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第35届中国控制会议

作者： XIN Jing RAN Bao-jing MA Xiao-min School of Automation & Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781509009107

To solve the robot visual servoing problem in the natural scene,a robot visual sliding servoing method using SIFT features in the framework of epipolar-geometry-based visual servoing is ***,corresponding image feature points from the current image feature and the desired image are obtained by SIFT algorithm;Then the features error of the whole robot visual servoing system are calculated according to the corresponding points;Finally,considering characteristics of epipolar geometry for robot visual servoing system,the rotation sliding mode controller and translation sliding mode controller are sequentially designed to calculate the rotation movement and translation movement of the robot *** positioning experiments on a 6DOF industrial robot demonstrate that the proposed method can effectively locate an object in the natural scene.

关键词： Epipolar geometry Visual servoing Sliding mode control SIFT features

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Highly dynamic and sensitive NEMOer calcium indicators for imaging ER calcium signals in excitable cells

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Nature Communications 2025年第1期16卷 1-12页

作者： Gu, Wenjia Chen, Jia-Hui Zhang, Yiyin Wang, Zhirong Li, Jia Wang, Sijia Zhang, Hanhan Jiang, Amin Zhong, Ziyi Zhang, Jiaxuan Xu, Ze Liu, Panpan Xi, Chao Hou, Tingting Gill, Donald L. Li, Dong Mu, Yu Wang, Shi-Qiang Tang, Ai-Hui Wang, Youjun Beijing Key Laboratory of Gene Resource and Molecular Development College of Life Sciences Beijing Normal University Beijing China Department of Anatomy School of Basic Medicine Anhui Medical University Anhui Hefei China State Key Laboratory of Membrane Biology College of Life Sciences Peking University Beijing China Institute of Neuroscience State Key Laboratory of Neuroscience Center for Excellence in Brain Science and Intelligence Technology Chinese Academy of Sciences Shanghai China National Laboratory of Biomacromolecules CAS Center for Excellence in Biomacromolecules Institute of Biophysics Chinese Academy of Sciences Beijing China Department of Cellular and Molecular Physiology Pennsylvania State University College of Medicine Hershey PA United States Anhui Province Key Laboratory of Biomedical Imaging and Intelligent Processing Institute of Artificial Intelligence Hefei Comprehensive National Science Center Hefei China Hefei National Research Center for Physical Sciences at the Microscale Division of Life Sciences and Medicine University of Science and Technology of China Hefei China Key Laboratory of Cell Proliferation and Regulation Biology Ministry of Education College of Life Sciences Beijing Normal University Beijing China

The Endoplasmic/sarcoplasmic reticulum (ER/SR) is central to calcium (Ca2+) signaling, yet current genetically encoded Ca2+ indicators (GECIs) cannot detect elementary Ca2+ release events from ER/SR, particularly in m...

The Endoplasmic/sarcoplasmic reticulum (ER/SR) is central to calcium (Ca²⁺) signaling, yet current genetically encoded Ca²⁺ indicators (GECIs) cannot detect elementary Ca²⁺ release events from ER/SR, particularly in muscle cells. Here, we report NEMOer, a set of organellar GECIs, to efficiently capture ER Ca²⁺ dynamics with increased sensitivity and responsiveness. NEMOer indicators exhibit dynamic ranges an order of magnitude larger than G-CEPIA1er, enabling 2.7-fold more sensitive detection of Ca²⁺ transients in both non-excitable and excitable cells. The ratiometric version further allows super-resolution monitoring of local ER Ca²⁺ homeostasis and dynamics. Notably, NEMOer-f enabled the inaugural detection of Ca²⁺ blinks, elementary Ca²⁺ releasing signals from the SR of cardiomyocytes, as well as in vivo spontaneous SR Ca²⁺ releases in zebrafish. In summary, the highly dynamic NEMOer sensors expand the repertoire of organellar Ca²⁺ sensors that allow real-time monitoring of intricate Ca²⁺ dynamics and homeostasis in live cells with high spatiotemporal resolution. © The Author(s) 2025.

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Sufficient and necessary conditions for Lyapunov stability of Lorenz system and their application

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Science China(Information Sciences) 2010年第8期53卷 1574-1583页

作者： LUO Qi 1 , LIAO XiaoXin 2 & ZENG ZhiGang 2 1 College of Information and control, Nanjing University of Information Science and Technology, Nanjing 210044, China 2 Department of control Science and Engineering, Huazhong University of Science and Technology, Image processing and intelligent control key laboratory of Education Ministry of China, Wuhan 430074, China College of Information and Control Nanjing University of Information Science and Technology Nanjing China Department of Control Science and Engineering Huazhong University of Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Wuhan China

The sufficient and necessary conditions for Lyapunov stability of the zero equilibrium point of Lorenz system are discussed, and some brief criteria are presented for globally exponential stability, globally asymptotical stability and instability. Furthermore, the behavior of the non-zero equilibrium point of Lorenz system is also investigated, and several sufficient and necessary conditions are provided for locally exponential stability and instability. The established theorems in this paper develop and extend the existing achievements on Lyapunov stability of Lorenz system. In conclusion, by applying the obtained results, some less conservative feedback-control laws are derived to guarantee the globally exponential stability of the chaos control of Chen system, Lu¨ system, Yang-Chen system and Yu-Xia Li system.

关键词： Lorenz system Lyapunov stability sufficient and necessary condition bifurcation values globally exponential synchronization

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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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Instance Reweighting Adversarial Training Based on Confused Label

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intelligent Automation & Soft Computing 2023年第8期37卷 1243-1256页

作者： Zhicong Qiu Xianmin Wang Huawei Ma Songcao Hou Jing Li Zuoyong Li Institute of Artificial Intelligence and Blockchain Guangzhou UniversityGuangzhou511442China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Minjiang UniversityFuzhou350121China

Reweighting adversarial examples during training plays an essential role in improving the robustness of neural networks,which lies in the fact that examples closer to the decision boundaries are much more vulnerable to being attacked and should be given larger *** probability margin(PM)method is a promising approach to continuously and path-independently mea-suring such closeness between the example and decision ***,the performance of PM is limited due to the fact that PM fails to effectively distinguish the examples having only one misclassified category and the ones with multiple misclassified categories,where the latter is closer to multi-classification decision boundaries and is supported to be more critical in our *** tackle this problem,this paper proposed an improved PM criterion,called confused-label-based PM(CL-PM),to measure the closeness mentioned above and reweight adversarial examples during ***-cally,a confused label(CL)is defined as the label whose prediction probability is greater than that of the ground truth label given a specific adversarial *** of considering the discrepancy between the probability of the true label and the probability of the most misclassified label as the PM method does,we evaluate the closeness by accumulating the probability differences of all the CLs and ground truth ***-PM shares a negative correlation with data vulnerability:data with larger/smaller CL-PM is safer/riskier and should have a smaller/larger *** demonstrated that CL-PM is more reliable in indicating the closeness regarding multiple misclassified categories,and reweighting adversarial training based on CL-PM outperformed state-of-the-art counterparts.

关键词： Reweighting adversarial training adversarial example boundary closeness confused label

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Research on Autonomous Foot Movement Recognition Based on SVM 2022

Research on Autonomous Foot Movement Recognition Based on SV...

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7th International Conference on Multimedia and Image processing, ICMIP 2022

作者： Meng, Tongning Zhao, Li Zhang, Zhiwen He, Xinglin Tianjin Key Laboratory of Information Sensing and Intelligent Control School of Automation and Electrical Engineering Intelligent Information Processing Tianjin300222 China

ISBN: (纸本)9781450387408

In order to improve the effectiveness of rehabilitation of stroke patients, active training can be used to treat and recover the patient's foot dyskinesia. Recognizing the different movement characteristics of the feet is an important part of the active rehabilitation of stroke patients. In this paper, the EMG signals of different movements of the right foot are classified and studied. The EMG signals of three different movement states of the foot resting state, foot stretched 15° and foot stretched 45° are collected, absolute mean and filter common space mode were used for feature extraction of EMG signal, and support vector machine (SVM) was used for classification and recognition after extraction. The experimental results show that the classification accuracy rate of resting state-foot-stretched 45° is 89.9%, which exceeds the classification accuracy rate of resting state-foot-stretched 15° of 86.8%. It shows that when the subjects stretch the foot at 45°, more motion units are activated and the characteristics are more obvious than when the feet are stretched at 15°. Therefore, by classifying the characteristics of EMG signals and identifying different autonomic movements of feet, it can be used as the basis for rehabilitation treatment of stroke patients. At the same time, the average classification accuracy of 15°-45 ° and the resting state-15 °-45 ° is above 80%, which confirms the feasibility of the signal processing method and support vector machine classification algorithm used in this paper for the study of automatic foot motion recognition. © 2022 ACM.

关键词： Support vector machines

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Unraveling the heterogeneity of solid electrolyte interphase kinetically affecting lithium electrodeposition on lithium metal anode

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Journal of Energy Chemistry 2023年第10期85卷 181-190,I0007页

作者： Mengyuan Zhou Yaqi Liao Longhui Li Ruoyu Xiong Guancheng Shen Yifu Chen Tianlun Huang Maoyuan Li Huamin Zhou Yun Zhang State Key Laboratory of Materials Processing and Die&Mould Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyWuhan 430074HubeiChina Guangdong Key Laboratory of Modern Control Technology Institute of Intelligent ManufacturingGuangdong Academy of SciencesGuangzhou 510075GuangdongChina

The stability and uniformity of solid electrolyte interphase(SEI)are critical for clarifying the origin of capacity fade and safety issues for lithium metal anodes(LMA).However,understanding the interplay of SEI heterogeneity and Li electrodeposition is limited by the coupling of complex electrochemistry and mechanics ***,the correlation between the SEI failure behavior and Li deposition morphology is investigated through a quantitative electrochemical-mechanical *** local deformation and stress of SEI during Li electrodeposition identify that the heterogeneous interface between different components first *** with the well-known mechanical strength,component uniformity plays the most important role in the initial SEI failure and uneven Li deposition,and a relative component uniformity(p>0.01)represents a proper balance to ensure the stability of the naturally heterogeneous ***,the component regulation of SEI via the designed electrolyte experimentally demonstrates that improving component uniformity benefits SEI stability and the uniform Li electrodeposition for LMA,thereby increasing the capacity by~20%after 300 *** fundamental understandings and proposed strategy can be not only used to guide the SEI optimization via the electrolyte regulation,but also extended to the rational designs of artificial SEI for high-performance LMA.

关键词： Li metal anode Solid electrolyte interphase Component uniformity Electrochemical-mechanical model Failure mechanism

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Predicting Remaining Useful Life of Industrial Equipment Based on Multivariable Monitoring Data Analysis

Predicting Remaining Useful Life of Industrial Equipment Bas...

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2018 Chinese Automation Congress, CAC 2018

作者： Li, Xin Xie, Guo Liu, Han Wang, Wenqing Information Processing Xi 'An University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Xi'an China

ISBN: (纸本)9781728113128

Modern industrial equipment plays a vital role in the operation of large industrial systems. Accurate prediction of its remaining useful life will greatly reduce the possibility of unsafe accidents. The internal structure of modern industrial equipment is very complex, and a variety of state monitoring data affect the remaining useful life of the equipment, and the mutual influence between different monitoring data has greatly increased the difficulty of remaining useful life prediction. In this paper, the long short-term memory network in deep learning is used to solve this problem. The long short-term memory network has many advantages in time series prediction. The remaining useful life prediction model of industrial equipment based on long short-term memory network and multivariable monitoring data is established, and aiming at the characteristics of multivariable monitoring data, Mini-batch Gradient Descent algorithm (MBGD) is adopted to train the network. Finally, the engine monitoring data set provided by the NASA prediction center is used to verify the algorithm. The data set is divided into training set and test set, the training set is put into the long short-term memory network to get the prediction model, and then the remaining useful life prediction is carried out by the test set. The prediction accuracy and generalization ability of the algorithm are verified by predicting the remaining useful life of three different turbofan engines. © 2018 IEEE.

关键词： Long short-term memory

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Passivity-Based Robust control Against Quantified False Data Injection Attacks in Cyber-Physical Systems

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1440-1450页

作者： Yue Zhao Ze Chen Chunjie Zhou Yu-Chu Tian Yuanqing Qin Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Computer Science Queensland University of TechnologyBrisbane QLD 4001Australia

Secure control against cyber attacks becomes increasingly significant in cyber-physical systems(CPSs).False data injection attacks are a class of cyber attacks that aim to compromise CPS functions by injecting false data such as sensor measurements and control *** quantified false data injection attacks,this paper establishes an effective defense framework from the energy conversion ***,we design an energy controller to dynamically adjust the system energy changes caused by unknown *** designed energy controller stabilizes the attacked CPSs and ensures the dynamic performance of the system by adjusting the amount of damping ***,with the disturbance attenuation technique,the burden of control system design is simplified because there is no need to design an attack *** addition,this secure control method is simple to implement because it avoids complicated mathematical *** effectiveness of our control method is demonstrated through an industrial CPS that controls a permanent magnet synchronous motor.

关键词： Cyber-physical systems energy controller energy conversion false data injection attacks L2 disturbance attenuation technology

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