检索结果-内蒙古大学图书馆

Field-Free Current-Induced Switching of L10-FePt Using Interlayer Exchange Coupling for Neuromorphic Computing

Physical Review Applied 2023年第2期19卷 024034-024034页

作者： Kaifeng Dong Zhe Guo YiYi Jiao Ruofan Li Chao Sun Ying Tao Shuai Zhang Jeongmin Hong Long You 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 School of Optical and Electronic Information and Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Wuhan 430074 China

L10-phase FePt is well known for its unusually robust perpendicular magnetic anisotropy (PMA) properties arising from strong conduction-electron spin-orbit coupling (SOC) with the Fe orbital moment. The strong PMA enables stable magnetic storage and memory devices with ultrahigh capacity. Meanwhile, SOC is also the premise of the recently discovered spin-orbit-torque (SOT) effect, which opens avenues for possible electrical manipulation of magnetization for L10-FePt. The bulk SOT of the L10-FePt single layer was discovered recently; this leads to the magnetization of L10-FePt reversibly switching on itself. However, deterministic SOT switching of bulk perpendicularly magnetized FePt magnets relies on an external magnetic field to break the symmetry. Here, the symmetry-breaking issue is resolved by interlayer exchange coupling, where the FePt layer is coupled with an in-plane magnetized NiFe layer through a TiN spacer layer. Furthermore, our device also presents memristive or gradual switching behaviors, even without an external field, offering the potential for constructing spin synapses and spin neurons for neuromorphic computing. An artificial neural network with high accuracy (∼91.17%) is realized based on the constructed synapses and neurons. Our work paves the way for field-free SOT switching of single bulk PMA magnets and their potential applications in neuromorphic computing.

关键词： Exchange interaction Magnetic anisotropy Magnetization switching Spin-orbit torque Spintronics

来源：评论

学校读者我要写书评

暂无评论

Hand Gesture Recognition from an Open-Set Perspective

引用

IEEE Transactions on Multimedia 2025年

作者： Zhou, Jun Xu, Chi Cheng, Li China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Vision and Learning Laboratory Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

Existing hand gesture recognition methods predominantly rely on a close-set assumption, which in essence limits the viewpoints, gesture categories, and hand shapes at test time to closely resemble those seen during training. This requirement is however rarely met in practice, as images are often captured from unconstrained viewpoints, with novel gestures and unseen hand shapes that can differ significantly from the training data. This motivates us to investigate an open-set hand gesture recognition problem, where hand gestures are still recognizable from unconstrained viewpoints, and novel gesture classes and hand shapes can be incrementally learned with just a few examples. To address this, we propose a viewpoint influence elimination network that extracts view-independent features, significantly improving performance in scenarios with unconstrained viewpoints. Moreover, a joint-weighted classification scheme is introduced to augment the cosine similarity metric for evaluating few-shot incremental learning of novel gestures and shapes. Finally, as existing hand gesture recognition datasets primarily adhere to the close-set assumption, a new hand gesture recognition dataset, OHG, is introduced in this paper, that includes a wide range of viewpoints, diverse gesture classes, and distinct hand shapes. Experimental hand gesture recognition results demonstrate the superior performance of our approach in both unconstrained viewpoint and few-shot incremental learning scenarios. The source code and the OHG dataset are to be made available at https://***/zhoujun-7/OSHGR. © 1999-2012 IEEE.

关键词： Palmprint recognition

来源：评论

学校读者我要写书评

暂无评论

Speech Emotion Recognition Based on Syllable-Level Feature Extraction

SSRN

引用

SSRN 2023年

作者： Rehman, Abdul Liu, Zhen-Tao Wu, Min Cao, Wei-Hua Jiang, Cheng-Shan 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

Speech emotion recognition systems have high computational requirements for deep learning models and low generalizability mainly because of the poor reliability of emotional measurements across multiple corpora. To solve these problems, we present a speech emotion recognition system based on a reductionist approach of decomposing and analyzing syllable-level ***-spectrogram of an audio stream is decomposed into syllable-level components, which are then analyzed to extract statistical features. The proposed method uses formant attention, noise-gate filtering, and rolling normalization contexts to decrease contextual differences and increase focus the attention on the structure of a formant. A set of syllable-level formant features is extracted and fed into a single hidden layer neural network that makes predictions for each syllable as opposed to the conventional approach of using a sophisticated deep learner to make sentence-wide *** syllable level predictions help to lower the aggregated error in utterance level cross-corpus predictions. The experiments on IEMOCAP (IE), MSP-Improv (MI), and RAVDESS (RA) databases show that the method archives better than the state-of-the-art cross-corpus unweighted accuracy of 47.6% for IE to MI and 56.2% for MI to IE. © 2023, The Authors. All rights reserved.

关键词： forecasting

来源：评论

学校读者我要写书评

暂无评论

Anomaly Detection and Alarm Limit Design for In-Hole Bit Bounce Based on Interval Augmented Mahalanobis Distance 1

引用

Proceedings of the 4th International Conference on Neural Computing for advanced Applications, NCAA 2023

作者： Hu, Bin Hu, Wenkai Zhang, Peng Cao, Weihua 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

ISBN: (数字)9789819958474

ISBN: (纸本)9789819958467

Timely and accurate anomaly detection is of great importance for the safe operation of the drilling process. To detect bit bounce during the drilling process, this paper proposes a method based on interval augmentation Mahalanobis distance. The method first selects process variables that are closely related to bit bounce through mechanism analysis;secondly, data augmentation is performed on the selected data;then, the Mahalanobis distance statistic of normal data is calculated and its distribution threshold is designed using the Kernel Density Estimation method;finally, the Mahalanobis distance is calculated for the augmented online data and compared to the threshold to determine if a bit bounce is present. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Anomaly detection

来源：评论

学校读者我要写书评

暂无评论

A Novel Ceramic Surface Based Constant force control Method for Flatness Inspection

SSRN

引用

SSRN 2023年

作者： Chen, Xin Gao, Xu Zhou, Yang Qin, Lang 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

A constant force control method of the robot based on a force sensor is proposed for the difficult point of high difficulty and low accuracy of ceramic surface flatness inspection. This paper proposed a method that combines a constant impedance controller for normal contact force with a posture compliance controller. The method decomposes force control and position control orthogonally to simplify the complex three-dimensional surface model of ceramics. The method solves the problem that the end-effector is difficult to be perpendicular to the contact surface due to the change of ceramic surface shape. Moreover, the proposed method can also detect whether the ceramic surface is flat or not by the change of the force sensor's indication and the change of the actual end position of the robot arm. Finally, the defect detection experiments are conducted on a plane and on a complex surface, respectively. The experiments demonstrate the adaptability and fast convergence of the method proposed in this paper, which meets the needs of high precision and fast response of industrial processes. © 2023, The Authors. All rights reserved.

关键词： force control

来源：评论

学校读者我要写书评

暂无评论

A Novel YJQR-LSTM Model for Nonparametric Probabilistic Sustainable Agriculture Wind Power forecasting Based on intelligent IoT

引用

IEEE Internet of Things Journal 2024年

作者： Wang, Jie Jiang, Junhui Chen, Xinlong Cai, Defu Wu, Yue Lu, Renzhi School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Harbin Engineering University College of Computer Science and Technology Harbin150001 China State Grid Hubei Electric Power Research Institute Hubei Wuhan430079 China School of Technology State Key Laboratory of Efficient Production of Forest Resources Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation Beijing Forestry University Beijing100083 China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China State Key Laboratory of Mechanical Transmission for Advanced Equipment Chongqing University Chongqing400044 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Energy costs associated with the consumption of non-renewable energy sources have become an important issue in improving the international competitiveness of agriculture. Wind power, as a renewable energy source, can replace non-renewable energy sources to reduce energy costs and improve the sustainability of agricultural. However, the inherent intermittency, randomness, and volatility within weather conditions and wind speed presents a substantial challenge in accurately predicting wind power generation. This work proposes a novel YJQR-LSTM algorithm that leverages Yeo-Johnson quantile regression (YJQR) with a long short-term memory (LSTM) network for nonparametric probabilistic forecasting of wind power generation via the intelligent Internet of Things. First, an improved YJQR model based on the YJ transformation is designed to obtain a more precise characterization of wind uncertainty, providing a more flexible probability density function for wind power generation. Then, utilizing the unique structure of the LSTM network to learn the parameters of the YJQR model, temporal features can be extracted from time series data. To mitigate the impact of outliers in the raw data on accuracy and improve computational efficiency, a novel logarithmic likelihood function is developed as the loss function utilized in the training phase. The effectiveness of the proposed algorithm is validated using a real-world dataset from five wind farms from the Global Energy forecasting Competition. Numerical results demonstrate that the algorithm provides more accurate wind power prediction results in complex wind power data environments, which is important for making full use of wind energy and thus reducing the consumption of non-renewable energy in agriculture. © 2024 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Large-Scale Hyperspectral Image Clustering Using Contrastive Learning

Large-Scale Hyperspectral Image Clustering Using Contrastive...

引用

2021 International Conference on Information and Knowledge Management Workshops, CIKMW 2021

作者： Cai, Yaoming Liu, Yan Zhang, Zijia Cai, Zhihua Liu, Xiaobo School of Computer Science China University of Geosciences Wuhan430074 China School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China

Unsupervised hyperspectral image (HSI) classification is an important but challenging task in the hyperspectral processing community. Despite great success, previous HSI clustering approaches belong to offline clustering which is often performed in a transductive scheme, thus failing to generalize to large-scale and unseen scenes. In this paper, we propose an online and deep clustering model for large-scale HSI clustering, termed spectral-spatial contrastive clustering (SSCC). Specifically, SSCC performs contrastive learning based on a series of semantic-preserving spectral-spatial augmentation to simultaneously maximize the intra-class agreement and inter-class variation, which are implemented by an instance-level contrastive loss and a cluster-level contrastive loss, respectively. The SSCC model is trained in an end-to-end fashion with minibatch, allowing it to efficiently handle large-scale HSIs. We assess the performance of SSCC on real HSI and show that SSCC significantly advances the state-of-the-art results with 8.41% improvement on accuracy. © 2021 CEUR-WS. All rights reserved.

关键词： Spectroscopy

来源：评论

学校读者我要写书评

暂无评论

A new result for H∞ performance analysis of sampled-data systems via looped-functionals

A new result for H∞ performance analysis of sampled-data sy...

引用

第41届中国控制会议

作者： Du Xiong Wen-Hu Chen Yong-He Lao Yu-Long Fan Chuan-Ke Zhang 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

This paper is concerned with H performance analysis of aperiodic sampled-data systems by employing the input delay ***,a novel augmented looped-functional（ALF） is presented under the double-side looped-functional technique,which considers coupled relationships among state vectors more fully than the current ***,by using the BesselLegendre inequality to estimate the derivative of the ALF,a stability criterion is derived in the form of linear matrix ***,a numerical example demonstrates the effectiveness and the advantages of the proposed criterion by comparing it with the existing ones.

关键词： Aperiodic sampled-data systems Stability analysis Input delay approach H_∞ performance Bessel-Legendre inequality

来源：评论

学校读者我要写书评

暂无评论

RGB-infrared fusion tracking algorithm based on Siamese network 2

RGB-infrared fusion tracking algorithm based on Siamese netw...

引用

2nd International Conference on Computer Vision, Image, and Deep Learning

作者： Li, Ruyou Cui, Wennan Wang, Zhiyong Zhang, Jingjing School of Automation China University of Geosciences Wuhan430074 China Key Laboratory of Intelligent Infrared Perception Chinese Academy of Sciences 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

ISBN: (数字)9781510646827

ISBN: (纸本)9781510646810

The target tracking method based on RGB image is affected by many factors such as light and haze weather, so it is difficult to distinguish the tracking target from the background, and it is easy to lead to the drift or even loss of the tracking target. Target tracking based on infrared images is not affected by light, haze and other illumination factors, but the target's color, texture and other characteristic information will be missing. Therefore, in order to obtain the target's color, texture and other characteristic information in a poorly illuminated environment, while achieving accurate and fast tracking of the object, this paper proposes a RGB and infrared image fusion tracking method based on a deep convolutional network. Firstly, the fusion method of RGB and infrared images is studied;secondly, a target tracking network based on the Siamese network is established to extract the image convolution features of the target template and the current target;finally, the response map is calculated by the deep cross-correlation module. At last, the performance test of the target tracking algorithm is carried out on the VOT2019RGBT data set. Experimental results show that the algorithm can effectively solve the problem of target tracking when the target is partially occluded, the tracking scene has no suitable illumination or the light changes strongly, and it is of great significance to improve the accuracy of target tracking under complex backgrounds. © 2021 SPIE.

关键词： Image fusion

来源：评论

学校读者我要写书评

暂无评论

Fuzzy PID control for suppressing stick-slip vibration of drill-string system

Fuzzy PID control for suppressing stick-slip vibration of dr...

引用

2022 Chinese automation Congress, CAC 2022

作者： Hu, Shuaikang Lu, Chengda Wu, Min He, Zhaoqing Song, Haitao Li, Wangnian School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Xi’an Research Institute Co. Ltd. China Coal Technology and Engineering Group Xi’an710077 China

ISBN: (纸本)9781665465335

In this paper, a fuzzy PID (Proportional Integral Derivative) controller is introduced to suppress the stick-slip vibration present in the drilling process. First, the dynamical model of stick-slip vibration is composed of the multi-DOF (Degree-Of-Freedom) drill-string model and the Karnopp model describing the interaction of the drill bit with the rock. Then, stability analysis is made for the initial PID parameters of our controller. To suppress the stick-slip vibration and at the same time mitigate the effects of the stratigraphic environment variation on the control performance, the fuzzy adaptive algorithm is chosen as the method of optimization controller parameters. From the experimental results, it is clear that our controller has good control performance in the complex and changing stratigraphic environment. © 2022 IEEE.

关键词： controllers

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：