检索结果-内蒙古大学图书馆

International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Haoyu Li Leimin Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781665402460

This paper investigates a unified controller to solve the fixed-time anti-synchronization (FTAS) and preassigned-time anti-synchronization (PTAS) problems for chaotic neural networks. Under our controller, chaotic neural network can realize anti-synchronization within the fixed or preassigned time which greatly expands the practical application range of the anti-synchronization. In addition, sufficient conditions and time estimation on FTAS and PTAS are derived. Finally, the feasibility of the control scheme is proved via a numerical simulation.

关键词： Sufficient conditions Neural networks Estimation Numerical simulation Synchronization Cybernetics

来源：评论

学校读者我要写书评

暂无评论

UAV Remote Sensing Image Stitching 15th

UAV Remote Sensing Image Stitching

引用

15th International Conference on Natural Computation, Fuzzy systems and Knowledge Discovery, ICNC-FSKD 2019, co-located with the 5th International Conference on Harmony Search, Soft Computing and Applications, ICHSA 2019

作者： Wu, Hui Chen, Jun School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9783030324551

The majority of image stitching (include UAV remote sensing images stitching) models are homography matrix transformation function, which could effectively simulate the rigid transformation of 2D images in 3D coordinate system. In order to prevent the accumulation of alignment errors (drift) and the projection distortion in the multi-image stitching task, we proposes a novel UAV remote sensing image stitching access consisting of homography transformation and Helmert transformation. In the overlapping and non-overlapping region we utility homography transformation and Helmert transformation respectively. With proposed method the UAV remote sensing image stitching result has fewer alignment errors and less projection distortion. © Springer Nature Switzerland AG, 2020.

关键词： Remote sensing

来源：评论

学校读者我要写书评

暂无评论

Deep transfer learning-based decoder calibration for intracortical brain-machine interfaces

引用

Computers in Biology and Medicine 2025年第Pt A期192卷 110231-110231页

作者： Li, Xiao Dong, Xianxin Wang, Jun Mao, Haodong Tu, Xikai Li, Wei He, Jiping Li, Qiang Zhang, Peng Hubei Key Laboratory of Modern Manufacturing Quantity Engineering School of Mechanical Engineering Hubei University of Technology Wuhan430068 China Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China MoE Key Laboratory for Biomedical Photonics Collaborative Innovation Center for Biomedical Engineering School of Engineering Sciences Huazhong University of Science and Technology Hubei Wuhan China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan China Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China

Intracortical brain-machine interfaces (iBMIs) aim to establish a communication path between the brain and external devices. However, in the daily use of iBMIs, the non-stationarity of recorded neural signals necessitates frequent recalibration of the iBMI decoder to maintain decoding performance, which requires collecting and labeling a large amount of new data. To address this challenge and minimize the time needed for decoder recalibration, we proposed an active learning domain adversarial neural network (AL-DANN). This model leveraged a substantial volume of historical data alongside a small amount of current data (four samples per category) to calibrate the decoder. By incorporating domain adversarial and active learning strategies, the model effectively transferred knowledge from historical data to new data, reducing the demand for new samples. We validated the proposed method using neural signals recorded from three monkeys performing different movements in a classification task or a regression task. The results showed that the AL-DANN outperformed existing state-of-the-art methods. Impressively, it required only four new samples per category for decoder recalibration, leading to a recalibration time reduction of over 80 %. To our knowledge, this is the first study to incorporate deep transfer learning into iBMI decoder calibration, highlighting the significant potential of applying deep learning technologies in iBMIs. © 2025

关键词： Adversarial machine learning

来源：评论

学校读者我要写书评

暂无评论

Design of a novel flexible assistive hand exoskeleton 37

Design of a novel flexible assistive hand exoskeleton

引用

37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Li, Guotao Cheng, Long Gao, Zhengrun Lu, Jilong Zhao, Yanjiang Institute of Automation State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China Fudan University The National Clinical Research Center for Aging and Medicine Shanghai China Harbin University of Science and Technology Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin150080 China Intelligent Machine Institute Harbin University of Science and Technology Harbin150080 China

ISBN: (纸本)9781665465366

Hand paralysis caused by stroke, spinal cord injury, or neurological trauma has a significant impact on the independence and quality of life of the patients. The hand exoskeleton can provide hand assistance and improve the patient's grasp. In this article, a novel wearable flexible hand exoskeleton is proposed to assist users in activities of daily life. To create a simple and lightweight assistive hand exoskeleton, 3D printing is used to manufacture most of the components, and a remote drive system is designed to reduce the weight of the hand exoskeleton. A ball pair device and a slider device are used to ensure the freedom of the thumb and the adaptability of the hand exoskeleton to different hand sizes. Finally, the experiments are conducted to verify that the hand exoskeleton can achieve motion assistance. © 2022 IEEE.

关键词： 3D printing

来源：评论

学校读者我要写书评

暂无评论

Downhole condition identification for geological drilling processes based on qualitative trend analysis and expert rules 1

引用

1st International Conference on Neural Computing for advanced Applications, NCAA 2020

作者： Li, Yupeng Cao, Weihua Hu, Wenkai Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (数字)9789811576706

ISBN: (纸本)9789811576690

In geological drilling processes, downhole incidents usually pose a serious threat to drilling safety. In order to improve the performance of drilling safety monitoring, a systematic downhole condition identification method is proposed based on the Qualitative Trend Analysis (QTA) and expert rules. Qualitative trends directly related to downhole conditions are extracted by QTA. Then, the existing expert rules to identify downhole conditions are summarized to create a knowledge base. The qualitative trends extracted from historical drilling data serve as new rules to extend the knowledge base. for online application, with new data collected, the qualitative trends are calculated, and then the downhole condition can be identified by querying the knowledge base. The effectiveness and practicality of the proposed method are demonstrated by case studies involving real drilling processes. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Geology

来源：评论

学校读者我要写书评

暂无评论

Learning to Find Good Correspondences Based on Global and Local Attention Mechanism

Learning to Find Good Correspondences Based on Global and Lo...

引用

2021 China automation Congress, CAC 2021

作者： Chen, Jun Gu, Yue Luo, Linbo School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan China

ISBN: (纸本)9781665426473

We are committed to designing a method for establishing a set of reliable correspondences between two images in this paper. Previous work proposes an outlier removal network based on global and local attention mechanism. It normalizes the feature map under the guidance of attention weight, as a result the robustness to outliers is improved and inliers are better preserved. However, element-wise multiplication of these two different attentions makes them unable to perform their original functions. In order to overcome this limitation, a network based on attention mechanism has been designed in our work. Firstly, global attention is employed to compute a global weight which can help normalization focus on inliers and reduce the influence of outliers on context information. Secondly, to extract channel information, we use local attention to learn a channel weight for each correspondence. Finally, the above structures and residual network modules are combined for correspondence establishment. Experimental results show that our method is better than other SOTA methods. © 2021 IEEE

关键词： Computer vision

来源：评论

学校读者我要写书评

暂无评论

Harmonic Disturbance Suppression for High-Performance Nonlinear Repetitive-control systems

引用

IFAC-PapersOnLine 2023年第2期56卷 4545-4550页

作者： Shengnan Tian Kang-Zhi Liu Manli Zhang Chengda Lu Min Wu Jinhua She 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 Department of Electrical and Electronic Engineering Chiba University Chiba 263-8522 Japan School of Engineering Tokyo University of Technology Hachioji Tokyo 192-0982 Japan

This study focuses on the performance design issue of nonlinear repetitive control (RC) systems subject to harmonic disturbances. First, a Takagi-Sugeno fuzzy model is used to describe a nonlinear plant. Then, a repetitive controller featuring a harmonic disturbance period is integrated with an EID estimator to form an RC-EID structure. The structure has a learning feature that gradually reduces the harmonic disturbance estimation error by self-learning. The linear inequality matrices guarantee the stability of nonlinear RC systems. A case study with two permanent magnet synchronous motors shows that the presented RC-EID estimator enhances the harmonic disturbance-suppression performance while compensating for the phase lag caused by the conventional EID filter.

关键词： Nonlinear repetitive control systems harmonic disturbance suppression equivalent input disturbance performance enhancement

来源：评论

学校读者我要写书评

暂无评论

Short - Term Prediction of Coke Pushing Current Peak Based on Improved ARIMA Model

Short - Term Prediction of Coke Pushing Current Peak Based o...

引用

Industrial Cyber-Physical systems (ICPS)

作者： Haiyang Wei Luefeng Chen Jie Hu Yi Ren Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Tokyo Institute of Technology Yokohama Japan

Coke pushing current is an indicator to evaluate the difficulty of coke pushing operation. The higher coke pushing current is, the greater coke pushing resistance is, and the more difficult coke is to push out. Accurate prediction of current peak during future coke pushing operation can provide more time for production personnel to adjust production status and avoid difficult coke pushing in carbonization chamber. In this paper, a combination prediction model based on VMD (Variational Mode Decomposition) and improved ARIMA (Autoregressive Integrated Moving Average) models is proposed. Firstly, VMD algorithm is used to decompose time series of coke pushing current peak, de-noising data, and extracting main information of time series. Then, ARIMA model is used to predict mean change of linear elasticity and GARCH (Generalized Autore-gressive Conditional Heteroskedasticity) model is introduced to predict ARIMA model residual and improve heteroscedasticity of nonlinear part of time series, and then ARIMA-GARCH model is established. Finally, predicted value is obtained by the sum of each component prediction. The experimental results show that the proposed prediction model has a high prediction accuracy in the short-term prediction of coke pushing current peak. The scheme is applied to actual coking production to guide production of coke.

关键词： Resistance Ovens Time series analysis Noise reduction Production Predictive models Prediction algorithms

来源：评论

学校读者我要写书评

暂无评论

Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

引用

Chinese control Conference (CCC)

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China 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 Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Explainable Deep Learning for Semg-Based Similar Gesture Recognition: A Shapley-Value-Based Solution

SSRN

引用

SSRN 2023年

作者： Wang, Feng Ao, Xiaohu Wu, Min Kawata, Seiichi She, Jinhua 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 School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

Surface electromyography (sEMG) based gesture recognition shows promise in enhancing human-robot interaction. However, accurately recognizing similar gestures is a challenging task, and the underlying mechanisms of gesture recognition are not well understood. To address these issues, we developed a new solution called the Shapley-value-based similar gesture recognition (SV-SGR) method. Our solution combines deep learning and game theory to achieve high recognition accuracy and interpretability. First, we devised a data preprocessing method that converts sEMG signals into sEMG color images, which can be more effectively utilized by deep learning techniques. Next, we established a deep-neural-network-based model for gesture recognition using the processed sEMG color images. Then, we designed a global explanation approach based on Shapley values to quantify the contribution of each channel to recognizing similar gestures. Finally, we carried out an explanation analysis, which provides feedback on the recognition model to enhance the precision of gesture recognition. Extensive comparisons and interpretable analyses have been conducted on real-world datasets, and the results demonstrate that the SV-SGR method outperforms other baselines under various experimental conditions. The interpretable analysis method based on Shapley values effectively enhances the performance of recognizing similar gestures and provides valuable insights into the decision-making process of recognition models. © 2023, The Authors. All rights reserved.

关键词： Gesture recognition

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：