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Current-Induced Magnetic Switching in an L1_(0) FePt Single Layer with Large Perpendicular Anisotropy Through Spin–Orbit Torque

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Engineering 2022年第5期8卷 55-61页

作者： Kaifeng Dong Chao Sun Laizhe Zhu Yiyi Jiao Ying Tao Xin Hu Ruofan Li Shuai Zhang Zhe Guo Shijiang Luo Xiaofei Yang Shaoping Li Long You School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of GeosciencesWuhan 430074China School of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China China Resources Microelectronics Limited Shanghai 200072China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518000China Wuhan National High Magnetic Field Center Huazhong University of Science and TechnologyWuhan 430074China

In this study,current-induced partial magnetization-based switching was realized through the spin–orbit torque(SOT)in single-layer L1_(0) FePt with a perpendicular anisotropy(K_(u⊥))of 1.19×10^(7) erg·cm^(-3)(1 erg·cm^(-3)=0.1 J·m^(-3)),and its corresponding SOT efficiency(βDL)was 8×10^(-6) Oe·(A·cm^(-2))^(-1)(1 Oe=79.57747 A·m^(-1)),which is several times higher than that of the traditional Ta/CoFeB/MgO structure reported in past *** SOT in the FePt films originated from the structural inversion asymmetry in the FePt films since the dislocations and defects were inhomogeneously distributed within the ***,the FePt grown on MgO with a granular structure had a larger effective SOT field and effi-ciency than that grown on SrTiO_(3)(STO)with a continuous *** SOT efficiency was found to be considerably dependent on not only the sputtering temperature-induced chemical ordering but also the lattice mismatch-induced evolution of the *** findings can provide a useful means of efficiently electrically controlling a magnetic bit that is highly thermally stable via SOT.

关键词： L1_(0)FePt SOT Inversion asymmetry Magnetic switching Perpendicular anisotropy

Stability and bifurcation control of fractional-order coupled Hindmarsh-Rose neural networks

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Stability and bifurcation control of fractional-order couple...

第42届中国控制会议

作者： Feng Liu Feifan Zhou Wei Wang Gang Cai Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University School of Education Minzu University of China

This article investigates a fractional-order coupled Hindmarsh-Rose neural networks ***,the existence and stability of an equilibrium point in the system are ***,the periodic bifurcation behavior of the system on a twoparameter plane is studied,and numerical simulations show the existence of both non-chaotic and chaotic plus periodic bifurcation behavior on the two-parameter ***,a feedback controller was designed to stabilize the bifurcation point of the delayed system and increase the stable range of the system.

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MC-NeRF: Multi-Camera Neural Radiance Fields for Multi-Camera Image Acquisition systems

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arXiv 2023年

作者： Gao, Yu Su, Lutong Liang, Hao Yue, Yufeng Yang, Yi Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Neural Radiance Fields (NeRF) use multi-view images for 3D scene representation, demonstrating remarkable performance. As one of the primary sources of multi-view images, multi-camera systems encounter challenges such as varying intrinsic parameters and frequent pose changes. Most previous NeRF-based methods assume a unique camera and rarely consider multi-camera scenarios. Besides, some NeRF methods that can optimize intrinsic and extrinsic parameters still remain susceptible to suboptimal solutions when these parameters are poor initialized. In this paper, we propose MC-NeRF, a method that enables joint optimization of both intrinsic and extrinsic parameters alongside NeRF. The method also supports each image corresponding to independent camera parameters. First, we tackle coupling issue and the degenerate case that arise from the joint optimization between intrinsic and extrinsic parameters. Second, based on the proposed solutions, we introduce an efficient calibration image acquisition scheme for multi-camera systems, including the design of calibration object. Finally, we present an end-to-end network with training sequence that enables the estimation of intrinsic and extrinsic parameters, along with the rendering network. Furthermore, recognizing that most existing datasets are designed for a unique camera, we construct a real multi-camera image acquisition system and create a corresponding new dataset, which includes both simulated data and real-world captured images. Experiments confirm the effectiveness of our method when each image corresponds to different camera parameters. Specifically, we use multi-cameras, each with different intrinsic and extrinsic parameters in real-world system, to achieve 3D scene representation without providing initial poses. The Code and supplementary materials are available at https://***/MC-NeRF Copyright © 2023, The Authors. All rights reserved.

关键词： Parameter estimation

DR-WLC: Dimensionality Reduction cognition for object detection and pose estimation by Watching, Learning and Checking

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arXiv 2023年

作者： Gao, Yu Xu, Xi Jiang, Tianji Chen, Siyuan Yang, Yi Yue, Yufeng Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Object detection and pose estimation are difficult tasks in robotics and autonomous driving. Existing object detection and pose estimation methods mostly adopt the same-dimensional data for training. For example, 2D object detection usually requires a large amount of 2D annotation data with high cost. Using high-dimensional information to supervise lower-dimensional tasks is a feasible way to reduce datasets size. In this work, the DR-WLC, a dimensionality reduction cognitive model, which can perform both object detection and pose estimation tasks at the same time is proposed. The model only requires 3D model of objects and unlabeled environment images (with or without objects) to finish the training. In addition, a bounding boxes generation strategy is also proposed to build the relationship between 3D model and 2D object detection task. Experiments show that our method can qualify the work without any manual annotations and it is easy to deploy for practical applications. Source code is at https: //***/IN2-ViAUn/DR-WLC. Copyright © 2023, The Authors. All rights reserved.

关键词： Object detection

A Contribution-based Resource Allocation Scheme for Multi-population Methods in Dynamic Environments 2

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A Contribution-based Resource Allocation Scheme for Multi-po...

2nd International Conference on Industrial Artificial Intelligence, IAI 2020

作者： Peng, Mai Li, Changhe Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (数字)9781728182162

ISBN: (纸本)9781728182162

The multi-population method is a common method for solving dynamic optimization problems. However, to design an efficient multi-population method, one of the challenging issues is how to allocate computational resources between populations given a limited computing buget in dynamic environments. This paper designs a contribution-based resource allocation mechanism. In this mechanism, a contribution degree of a population is defined according to the performance of the population, which determines the probability of the population to obtain the computing resource. This mechanism is implemented in an adaptive multi-population method. Experimental results on the moving peaks benchmark show that the algorithm equipped with the resource allocation mechanism outperforms the original algorithms. © 2020 IEEE.

关键词： Resource allocation

CRRS: Concentric Rectangles Regression Strategy for Multi-point Representation on Fisheye Images

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arXiv 2023年

作者： Wang, Xihan Xu, Xi Gao, Yu Yang, Yi Yue, Yufeng Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Modern object detectors take advantage of rectangular bounding boxes as a conventional way to represent objects. When it comes to fisheye images, rectangular boxes involve more background noise rather than semantic information. Although multi-point representation has been proposed, both the regression accuracy and convergence still perform inferior to the widely used rectangular boxes. In order to further exploit the advantages of multi-point representation for distorted images, Concentric Rectangles Regression Strategy(CRRS) is proposed in this work. We adopt smoother mean loss to allocate weights and discuss the effect of hyper-parameter to prediction results. Moreover, an accurate pixel-level method is designed to obtain irregular IoU for estimating detector performance. Compared with the previous work for muti-point representation, the experiments show that CRRS can improve the training performance both in accurate and stability. We also prove that multi-task weighting strategy facilitates regression process in this design. Source code is at https://***/IN2-ViAUn/Concentric-Rectangles-Loss. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

Finite-Time Synchronization of Flux-controlled complex-Valued Memristive Neural Networks

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Finite-Time Synchronization of Flux-Controlled Complex-Value...

Neuromorphic Computing (ICNC), International Conference on

作者： Yonghuan Wang Leimin Wang Genping Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Wuhan Second Ship Design and Research Institute Wuhan China

In this paper, by using the flux-controlled memristor model, the finite-time synchronization problem of delayed complex-valued memristive neural networks (MCNNs) is studied. Firstly, according to the proposed memristor model, we model the MCNNs as continuous systems on voltage-flux-time $(\wp, \varpi, t)$ domain. Then, we design a class of approaches to realize state synchronization between the drive and response systems, and the corresponding synchronization conditions are achieved. Finally, the effectiveness of results is illustrated with the simulations.

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Fault diagnosis of drilling process based on multi-scale decomposition and decision fusion

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IFAC-PapersOnLine 2023年第2期56卷 8079-8084页

作者： Aoxue Yang Min Wu Wanke Yu Jie Hu Chengda Lu Yosuke Nakanishi School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China Graduate School of Environment and Energy Engineering Waseda University Tokyo 169-8555 Japan

Data-driven fault diagnosis methods have been widely applied at present. In the drilling process, there usually exists multiple failure modes resulting in the multi-scale of drilling fault data, which would bring challenges for the data-driven methods application in drilling. By considering the characteristics of multi-scale and multivariate, an original scheme based on mode decomposition and decision fusion is proposed for fault diagnosis of drilling process. Firstly, the raw data are decomposed and reconstructed into multiple groups of series. Then, for each group, the diagnosis model is established using the convolutional neural network (CNN), and several diagnostic results are obtained. Finally, all diagnostic results are fused by the Dempster-Shafer (D-S) evidence theory, and the fused result is taken as the final diagnostic result. The actual data based experiments illustrate the effectiveness of proposed method for improving the performance of drilling fault diagnosis.

关键词： Fault diagnosis drilling process multivariate variational mode decomposition decision fusion

Temperature Compensation Method of Fluxgate Sensor Based on Polynomial Fitting

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arXiv 2024年

作者： Yang, Ruiping Liu, Huan Ge, Jian Chugo, Daisuke Dong, Haobin 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 Faculty of Engineering Kwansai Gakuin University Osaka669-1330 Japan

Fluxgate sensors are widely used in the field of low frequency and weak vector magnetic field measurement because of their good performance, such as high resolution and low power consumption. However, during the long-term continuous observation, the drift errors of the fluxgate sensor will occur due to the variable ambient temperature. This paper proposes a temperature compensation method for fluxgate sensors based on polynomial fitting. First, a physical model of the temperature & fluxgate sensor was established on the COMSOL Multiphysics simulation platform, and the influence of temperature on the measurement performance of the fluxgate sensor was analyzed. Second, according to the existing temperature-magnetic field data, a temperature compensation model of the fluxgate sensor was constructed. And compared it with other temperature compensation method, the result shows that the proposed temperature compensation method is relatively simple and can better achieve real-time compensation for sensor application scenarios. Finally, to verify the effectiveness of the proposed method, numerous laboratory experiments were *** temperature drift is reduced from more than 500 nT before compensation to about 1 nT. The results show that the proposed method has a good temperature compensation effect on the data measured by the fluxgate sensor within a variable temperature background. Copyright © 2024, The Authors. All rights reserved.

关键词： Simulation platform