检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Tao, Ying Sun, Chao Li, Wendi Wang, Cen Jin, Fang Zhang, Yue Guo, Zhe Zheng, Yuhong Wang, Xiaoguang Dong, Kaifeng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Wuhan National Laboratory for Optoelectronics Huazhong University of Science & Technology Wuhan430074 China Changxin Memory Technologies Inc. Hefei230601 China

In this study, the memristor driven by spin-orbit torque (SOT) is realized in the bulk L1 0 FePt systems with high perpendicular magnetization anisotropy (PMA). Due to the domain nucleation and expansion driven by current pulses, multi-level Hall resistances can be continuously tuned by the current density, where the memristive states are retained by the domain wall pinning effects. The properties of multi-level resistances for samples with different structures are associated with the magnitude of field-like torque, and the larger efficiency of field-like torque enhances the multiple resistance characteristics. Furthermore, the memristive behaviors in the field-free condition are obtained by utilizing the interlayer exchange coupling. Finally, based on the memristive characteristics of our devices, the three-layer multilayer perceptron (MLP) neural network is built to perform the MNIST handwritten digit recognition task, and the accuracy of weight update can reach up to 88.55%. These results pave the way for the application of SOT-driven memristors in neuromorphic computing. © 2022, The Authors. All rights reserved.

关键词： Memristors

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An ensemble model based on weighted support vector regression and its application in annealing heating process

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Science China(Information Sciences) 2019年第4期62卷 203-205页

作者： Yongyue ZHANG Weihua CAO Yali JIN Min WU School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,In the steel industry, the annealing heating production directly impacts the economic benefits of enterprises; hence, accurately predicting the required gas flow is very important [1]. On account of high equipment complexity, it costs lots of time for maintaining a traditional mechanism model at a good working condition; data-driven model, such

关键词： SVR An ensemble model based on weighted support vector regression and its application in annealing heating process

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Simultaneously Calibration of Multi Hand-Eye Robot system Based on Graph

arXiv

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arXiv 2023年

作者： Zhou, Zishun Ma, Liping Liu, Xilong Cao, Zhiqiang Yu, Junzhi The Institute of Automation Chinese Academy of Sciences Beijing100190 China The College of Electrical Engineering and Computer Science Australian National University Canberra2601 Australia The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Turbulence and Complex System Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Peking University Beijing100871 China

Precise calibration is the basis for the vision-guided robot system to achieve high-precision operations. systems with multiple eyes (cameras) and multiple hands (robots) are particularly sensitive to calibration errors, such as micro-assembly systems. Most existing methods focus on the calibration of a single unit of the whole system, such as poses between hand and eye, or between two hands. These methods can be used to determine the relative pose between each unit, but the serialized incremental calibration strategy cannot avoid the problem of error accumulation in a large-scale system. Instead of focusing on a single unit, this paper models the multi-eye and multi-hand system calibration problem as a graph and proposes a method based on the minimum spanning tree and graph optimization. This method can automatically plan the serialized optimal calibration strategy in accordance with the system settings to get coarse calibration results initially. Then, with these initial values, the closed-loop constraints are introduced to carry out global optimization. Simulation experiments demonstrate the performance of the proposed algorithm under different noises and various hand-eye configurations. In addition, experiments on real robot systems are presented to further verify the proposed method. © 2023, CC BY-SA.

关键词： Multipurpose robots

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Distributed derivative-free learning method for stochastic optimization over a network with sparse activity

arXiv

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arXiv 2021年

作者： Li, Wenjie Assaad, Mohamad Zheng, Shiqi Paris Research Center Huawei Technologies France CentraleSupélec France Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China

This paper addresses a distributed optimization problem in a communication network where nodes are active sporadically. Each active node applies some learning method to control its action to maximize the global utility function, which is defined as the sum of the local utility functions of active nodes. We deal with stochastic optimization problem with the setting that utility functions are disturbed by some non-additive stochastic process. We consider a more challenging situation where the learning method has to be performed only based on a scalar approximation of the utility function, rather than its closed-form expression, so that the typical gradient descent method cannot be applied. This setting is quite realistic when the network is affected by some stochastic and time-varying process, and that each node cannot have the full knowledge of the network states. We propose a distributed optimization algorithm and prove its almost surely convergence to the optimum. Convergence rate is also derived with an additional assumption that the objective function is strongly concave. Numerical results are also presented to justify our claim. Copyright © 2021, The Authors. All rights reserved.

关键词： Stochastic systems

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Spin–Orbit Torque Induced Magnetization Switching of Heusler Alloy Co2fesi for Neuromorphic Computing

SSRN

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SSRN 2022年

作者： Zhao, Jiale Zhang, Shuai Li, Wendi Dong, Kaifeng Wang, Ke Guo, Zhe School of Optical and Electronic Information Huazhong University of Science and Technology Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Mechanical and Electronic Engineering East China University of Technology Nanchang330013 China

Spintronic devices have the advantages of high endurance and energy efficiency for nonvolatile memory and emerging neuromorphic computing applications, especially with the spin-orbit torque (SOT) driven magnetization switching manner. The Co-based Heusler alloy is potentially an ideal material for constructing spintronic devices due to its high spin polarization, high saturation magnetization, high Curie temperature and low damping. Here, we investigate the current induced magnetization switching of Heusler alloy Co 2 FeSi with good perpendicular magnetic anisotropy through SOT. Inspired by the gradual switching process, we further study the memristive behaviors of the device, which can be used as artificial synapse for neuromorphic computing. Both the pulse amplitudes and pulse numbers are exploited to modulate the resistance states. Based on the extracted synaptic characteristics, an artificial neural network is simulated, causing a high accuracy of 91.52%. Our work paves a way for the application of Heusler alloy in magnetic random-access memory and neuromorphic computing. © 2022, The Authors. All rights reserved.

关键词： Neural networks

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Motion Semantic Enhancement and Autonomous Information Mining for Static-Dynamic Visual Emotion Recognition in Human–Robot Interaction

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Cheng-Shan Jiang Zhen-Tao Liu Edwardo F. Fukushima Jinhua She School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Ministry of Education and Engineering Research Center of Intelligent Technology for Geo-Exploration China University of Geosciences Wuhan China School of Engineering Tokyo University of Technology Hachioji Japan

The advancement of static-dynamic visual emotion recognition (DVER) plays a pivotal role in the evolution of intelligent and empathetic machines. Currently, the progress of static visual emotion recognition (SVER) faces challenges, primarily the need to balance model efficiency with robust recognition performance. Moreover, obstacles such as noisy data and limited labeled datasets restrict models from effectively learning the appearance features and dynamic dependencies intrinsic to DVER. In the realm of SVER, facial pixel, and semantic representation are derived using a lightweight surface and landmark features embedding network, followed by neuron-energy-based feature fusion-filtering to enhance the fusion of semantic representations positively. For DVER, a Global Anchor-Dependent Noisy Emotional Data Filtering (GADNEF) method is employed for noisy label learning (NLL), facilitating clip-wise filtering of ambiguous data via iterative computations of frame-wise attention statistics across batches. Furthermore, a self-supervised learning (SSL) paradigm based on a unified appearance and motion-guided masked autoencoder (UAMGMAE) is implemented, enabling large-scale knowledge transfer tailored for video-based facial expression analysis. Our approach has achieved accuracies of 97.07%, 98.90%, 61.39%, and 92.28% on SVER datasets including KDEF, RaFD, SFEW, and RAF-DB, respectively, while the weighted average recall (WAR) and unweighted average recall (UAR) on DVER datasets such as DFEW and MAFW were 75.12%, 64.37%, 55.26%, and 42.53%, respectively. A preliminary application experiment has also been conducted to validate the practical applicability of our method within human–robot interaction (HRI) scenarios.

关键词： Noise measurement Visualization Emotion recognition Semantics Human-robot interaction Filtering Feature extraction Training Neurons Transformers

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Room Impulse Response Reshaping-Based Blind Source Separation in an Underdetermined Reverberant Environment

SSRN

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SSRN 2023年

作者： Xie, Yuan Zou, Tao Yang, Junjie Sun, Weijun Xie, Shengli School of Mechanical and Electrical Engineering Guangzhou University Guangdong-Hong Kong-Macao Key Laboratory of Multi-scale Information Fusion and Collaborative Optimization Control of Complex Manufacturing Process Guangzhou510006 China School of Automation Guangdong University of Technology Joint International Research Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education of the P.R.C. Guangzhou510006 China School of Automation Guangdong University of Technology Guangdong Key Laboratory of IoT Information Processing Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China School of Automation Guangdong University of Technology Key Laboratory of Intelligent Detection and the IoT in Manufacturing Ministry of Education 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China

Blind source separation in an underdetermined reverberation environment is a very challenging issue. The classical method is based on the expectation-maximization algorithm. However, it is limited in a high reverberation environment, resulting in bad or even invalid separation performance. To get rid of this restriction, a room impulse response reshaping-based blind source separation algorithm is designed to solve the signal separation problem in an underdetermined reverberant environment. Firstly, a room impulse response reshaping technology is designed to eliminate the influence of audible echo for the reverberant environment, improving the quality of the received signals. Then, a new mathematical model of time-frequency mixing signals is established to reduce the approximation error of model transformation caused by high reverberation. Furthermore, an improved expectation-maximization algorithm is proposed for real-time update learning rules of model parameters, and then the sources are separated using the estimators provided by the improved expectation maximization method. Experimental results based on source separation of speech and music mixtures demonstrate that the proposed algorithm achieves better separation performance while maintaining much better robustness than the popular expectation-maximization methods. © 2023, The Authors. All rights reserved.

关键词： Blind source separation

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Stability and Stabilization of T-S Fuzzy systems with Sampled-Data controller: A Fuzzy-Related Matrix Injection Method

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IEEE Transactions on Fuzzy systems 2025年

作者： Xiong, Du Zhang, Chuan-Ke Jin, Li Fan, Yu-Long He, Yong China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

This paper addresses the stability and stabilization issues of Takagi-Sugeno (T-S) fuzzy systems under sampled-data control. In this paper, efforts are dedicated to developing a stability criterion and control strategy with high accuracy and low complexity, leveraging an improved looped functional and a fuzzy-related matrix injection method. First, an improved looped function containing quadratic information about the sampling sawtooth characteristic is employed to include as much system state information as possible in a simple form. In response to the nonlinear terms encountered in the functional derivatives, a fuzzy-related matrix injection method is proposed on the basis of linearization transformation. This method enables the unified treatment of reciprocally convex and quadratic terms, which is conducive to reducing estimation gaps. Based on the aforementioned techniques, stability and stabilization criteria for T-S fuzzy systems are derived. The efficacy and superiority of the proposed method are substantiated through rigorous theoretical analysis and illustrative instances. © 1993-2012 IEEE.

关键词： Sampled data control systems

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Atf-Bss: Adaptive Time-Frequency Blind Source Separation for High Reverberation and Echo Environments

SSRN

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SSRN 2023年

作者： Xie, Yuan Zou, Tao Chen, Ci Sun, Weijun Xie, Shengli School of Mechanical and Electrical Engineering Guangzhou University Guangdong-Hong Kong-Macao Key Laboratory of Multi-scale Information Fusion and Collaborative Optimization Control of Complex Manufacturing Process Guangzhou510006 China School of Automation Guangdong University of Technology Joint International Research Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education of the P.R.C. Guangzhou510006 China School of Automation Guangdong University of Technology Guangdong Key Laboratory of IoT Information Processing Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China School of Automation Guangdong University of Technology Key Laboratory of Intelligent Detection and the IoT in Manufacturing Ministry of Education 111 Center for Intelligent Batch Manufacturing Based on IoT Technology Guangzhou510006 China

Blind source separation with high reverberation and echoes is an open and extremely challenging issue. Because the room reverberation and echoes have an important influence on acoustics quality, bringing great difficulty to the independent source separation. In the paper, an adaptive time-frequency blind source separation (ATF-BSS) algorithm is designed to deal with the high reverberation and echoes, which can adaptively attenuate the audible echoes and enhance the harmonic structure of the real-world audio signals, achieving excellent separation performance. Firstly, an equalizer network is designed for the room impulse response to weakening audible echoes under the high reverberation and echo environments without changing the perceived timbre. Furthermore, an adaptive time-frequency Wiener-like masking is presented to enhance the dominant signal and attenuate the other components having less energy than the dominant signal. To the best of our knowledge, this is the first attempt to incorporate the advantages of an equalizer network for removing or weakening audible echoes and adaptive time-frequency masking to solve blind separation with high reverberation and echoes. Experimental results on the public audio datasets demonstrate that the proposed ATF-BSS algorithm improves signal intelligibility and achieves much better separation performance than the state-of-the-art methods. © 2023, The Authors. All rights reserved.

关键词： Reverberation

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Low-Friction Soft Robots for Targeted Bacterial Infection Treatment in Gastrointestinal Tract

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Cyborg and Bionic systems 2024年第1期5卷 162-176页

作者： Ben Wang Yunrui Chen Zhicheng Ye Haidong Yu Kai Fung Chan Tiantian Xu Zhiguang Guo Weimin Liu Li Zhang College of Chemistry and Environmental Engineering Shenzhen UniversityShenzhen 518060China Guangxi Key Laboratory of Processing for Non-Ferrous Metals and Featured Materials School of ResourceEnvironments and MaterialsGuangxi UniversityNanning 530004China Chow Yuk Ho Technology Centre for Innovative Medicine The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARChina Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Key Laboratory of Biomedical Imaging Science and System Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China Hubei Collaborative Innovation Centre for Advanced Organic Chemical Materials and Ministry of Education Key Laboratory for the Green Preparation and Application of Functional Materials Hubei UniversityWuhan 430062China State Key Laboratory of Solid Lubrication Lanzhou Institute of Chemical PhysicsChinese Academy of ScienceLanzhou 730000China Department of Mechanical and Automation Engineering The Chinese University of Hong KongShatinNew TerritoriesHong Kong SARChina Multi-Scale Medical Robotics Center Hong Kong Science ParkShatinNew TerritoriesHong Kong SARChina

Untethered and self-transformable miniature robots are capable of performing reconfigurable deformation and on-demand locomotion,which aid the traversal toward various lumens,and bring revolutionary changes for targeted delivery in gastrointestinal(GI)***,the viscous non-Newtonian liquid environment and plicae gastricae obstacles severely hamper high-precision actuation and payload ***,we developed a low-friction soft robot by assembly of densely arranged cone structures and grafting of hydrophobic *** magnetic orientation encoded robot can move in multiple modes,with a substantially reduced drag,terrain adaptability,and improved motion velocity across the non-Newtonian ***,the robot stiffness can be reversibly controlled with magnetically induced hardening,enabling on-site scratching and destruction of antibiotic-ineradicable polymeric matrix in biofilms with a low-frequency magnetic ***,the magnetocaloric effect can be utilized to eradicate the bacteria by magnetocaloric effect under high-frequency alternating *** verify the potential applications inside the body,the clinical imaging-guided actuation platforms were developed for vision-based control and delivery of the *** developed low-friction robots and clinical imaging-guided actuation platforms show their high potential to perform bacterial infection therapy in various lumens inside the body.

关键词： gastrointestinal tract reconfigurable deformation targeted bacterial infection treatment low friction soft robots plicae gastricae obstacles assembly densely arranged cone structures targeted delivery grafting hy

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