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IEEE International Conference on Systems, Man and Cybernetics

作者： Lubin Meng Xue Jiang Tianwang Jia Dongrui Wu Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs, To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs.

关键词： Training Privacy Data privacy Accuracy Perturbation methods Machine learning Electroencephalography Brain-computer interfaces Protection Spectrogram

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High-Precision and Arbitrary-length Fixed-Point Fast Hartley Transform without Multiplications

High-Precision and Arbitrary-length Fixed-Point Fast Hartley...

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WRI International Conference on Communications and Mobile Computing, CMC

作者： Zhenbing Liu Jianguo Liu Guoyou Wang Key Laboratory of Education Ministry for Image Processing and Intelligent Control State Key Laboratory of Multispectral Information Processing Technologies Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

Discrete Hartley transform (DHT) is an important tool in digital signal processing. In this paper, based on our previous work of performing DHT via linear sums of discrete moments, we have made development to eliminate multiplications in discrete Hartley transforms by performing appropriate bit operations and shift in binary system, which can be implemented by integer additions of fixed points. An efficient and regular systolic array is designed to implement it, and the complexity analysis is also given. Different to other fast Hartley transforms, our algorithm can deal with arbitrary length signals and get high precision. The approach is also applicable to multi-dimensional DHT and DHT inverses.

关键词： Discrete transforms Signal processing algorithms Digital signal processing Systolic arrays Laboratories Educational technology Very large scale integration Hardware Mobile communication Mobile computing

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Global Asymptotic Synchronization of Coupled Neural Networks with Reaction Diffusions and Unbounded Time-varying Delays

Global Asymptotic Synchronization of Coupled Neural Networks...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yun Xing Yin Sheng The Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This article investigates global asymptotic synchronization of coupled neural networks with reaction diffusions and unbounded time-varying delays (RDUDCNNs). Through designing a centralized adaptive controller and corresponding updating laws of time-varying control gains, under two different upper bound of control gains, an asymptotic convergence lemma under unbounded time-varying delays and the Barbarat lemma are used to derive global asymptotic synchronization of RDUDCNNs, respectively. The effectiveness of the obtained conclusion is verified through a numerical simulation.

关键词： Upper bound Automation Neural networks Numerical simulation Delays Synchronization Convergence

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Thermal Safety Analysis and Dynamic control Strategy for Mode Switching Process of Reversible Solid Oxide Cell System

Thermal Safety Analysis and Dynamic Control Strategy for Mod...

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第42届中国控制会议

作者： Wei Zhao Guoqiang Liu Zexin Li Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology

Reversible solid oxide cells(rSOC) can operate in both electrolysis mode and in fuel cell mode with high efficiency and reduced cost using the same device for both *** used in dynamic operation with intermittent electrical power sources,rSOC system switches from the fuel cell(SOFC) to electrolyzer(SOEC) and vice versa depending on load and grid *** can lead to temperature profiles within the stack that can potentially lead to the failure of the stack and eventually the *** the present work,a system-level dynamic model of r SOC is established and validated against experimental ***,detailed dynamic thermal behavior of stack during the switching between the two modes is analyzed,and a temperature management controller based on Model Predict control method(MPC) is *** flow and temperature at the stack inlet are controlled by air flow and bypass valves,avoiding problems associated with temperature overshoot during transient *** simulation results show that the temperature controller has the ability to follow fast thermal changes while maintaining thermal safety,which indicates the competitiveness of the controller.

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3-D temperature field reconstruction of lithium-ion battery pack using real-time distributed moving horizon estimation

3-D temperature field reconstruction of lithium-ion battery ...

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第35届中国控制与决策会议

作者： Jiayu Yan Yiming Wan School of Artificial Intelligence and Automation Huazhong University of Science and Technologyand Key Laboratory of Image Processing and Intelligent ControlMinistry of Education

As lithium-ion batteries are widely used in different fields,the thermal effect is of serious *** to achieve accurate temperature estimation in real time is the main challenge of current *** address this problem,we propose a realtime distributed moving horizon estimation(RT-DMHE) based on partial differential equations describing thermal dynamics of a lithium-ion battery *** decomposes the real-time centralized moving horizon estimation(RT-CMHE) into multiple local estimators that run in parallel with information exchange from adjacent *** validation shows that the root mean square error of temperature estimates from the proposed RT-DMHE is smaller than that of an existing distributed Kalman filter in ***,compared to the RT-CMHE,the proposed RT-DMHE achieves comparable estimation accuracy while vastly reducing the average computation time per sample.

关键词： lithium-ion battery pack distributed moving horizon estimation real-time computation state-of-temperature estimation

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A Time-Independent control Method for Variable-Speed Load-Bearing Walking with Suspended Backpack

A Time-Independent Control Method for Variable-Speed Load-Be...

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第43届中国控制会议

作者： Zhiyuan He Yu Cao Yifei Guo Jian Huang Hubei Key Laboratory of Brain-inspired Intelligent Systems Key Laboratory for Image Processing and Intelligent ControlSchool of Artificial Intelligence and AutomationHuazhong University of Science and Technology

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

Walking with a load brings a significant burden to human shoulders,resulting in increasing metabolic energy consumption and the risk of skeleton and muscle *** backpack has been widely conducted for load-bearing walking,but exiting time-dependent control methods and event-based control methods are unable to exploit the characteristics of human gait *** this case,a time-independent control(TIC) method capable of eliminating the time dependence and adapting to variable speed is *** on the dynamical model of human-backpack system,an assistance profile along with the parameter optimization method are introduced which allows the backpack to reduce the burden on human shoulders during load-bearing *** the simulation evaluation,the proposed TIC method is compared with an impedance controller based time-dependent method and a locked backpack,under both constant speed and variable speed *** results demonstrates that the TIC case achieves an 89.1% reduction in dynamic load on shoulder under the condition of constant speed and a 78.2% reduction under the condition of variable speed,compared with the LOCKED case.

关键词： suspended backpack load carriage time-independent control

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Attention to refine through multi-scales for semantic segmentation

arXiv

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arXiv 2018年

作者： Yang, Shiqi Peng, Gang Key Laboratory of Ministry of Education for Image Processing and Intelligence Control School of Automation Huazhong University of Science and Technology Wuhan China

This paper proposes a novel attention model for semantic segmentation, which aggregates multi-scale and context features to refine prediction. Specifically, the skeleton convolutional neural network framework takes in multiple different scales inputs, by which means the CNN can get representations in different scales. The proposed attention model will handle the features from different scale streams respectively and integrate them. Then location attention branch of the model learns to softly weight the multi-scale features at each pixel location. More- over, we add an recalibrating branch, parallel to where location attention comes out, to recalibrate the score map per class. We achieve quite com- petitive results on PASCAL VOC 2012 and ADE20K datasets, which surpass baseline and related works. Copyright © 2018, The Authors. All rights reserved.

关键词： Semantic Segmentation

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Model Predictive control Method for Multi-motor System with Dead Zone

Model Predictive Control Method for Multi-motor System with ...

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作者： Genglin Fan Xiuchuan Tang Yi Shen Linan Deng China-EU Institute for Clean and Renewable Energy Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology School of Mechanical Science and Engineering Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology

The multi-motor system shows excellent performance in achieving high-precision control in the applications with large load inertia,such as large-aperture telescopes and highprecision processing machine ***,the non-linearity of gear transmission remains a key challenge that will cause the fluctuation of angular velocity and position of the load in the multi-motor *** order to compensate for the nonlinearity in the multi-motor system,this paper introduces a deadzone model into the spring-damper dynamics of the multi-motor system,based on which a model predictive control(MPC) method is proposed to control the angular velocity and angle of the *** optimization target of the proposed controller is to limit the fluctuations of input torque as much as *** effectiveness of the dead-zone based dynamic model and the MPC method are verified by simulation.

关键词： multi-motor system MPC dead zone

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Channel and Trials Selection for Reducing Covariate Shift in EEG-based Brain-Computer Interfaces

Channel and Trials Selection for Reducing Covariate Shift in...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： He He Dongrui Wu Key Laboratory for Image Processing and Intelligent Control Ministry of Education and the School of Artificial Intelligence and Automation Huazhong University of Science and Technology

ISBN: (纸本)9781728145709

This paper aims at reducing the calibration effort of EEG-based brain-computer interfaces (BCIs). More specifically, in the context of cross-subject classification, we correct covariate shift of EEG data from different subjects, so that a classifier trained on auxiliary subjects can also be applied to a new subject, without any labeled trials from the new subject. Methods: We propose two approaches to enhance the performance of a state-of-the-art Riemannian space transfer learning (TL) algorithm: 1) trials selection, which resamples trials from the auxiliary subjects so that they become more consistent with those of the new subject;and, 2) channel selection, which reduces the number of channels and hence makes the Riemannian space computations more accurate and efficient. Results: We tested the proposed approaches on two motor imagery datasets. The results verified that they can enhance the performance of the state-of-the-art TL algorithm. Conclusion and significance: Our proposed approaches make the state-of-the-art TL algorithm more effective and efficient.

关键词： Brain-Computer Interfaces experimentation Trials Computer interfaces Thallium Shift Classifiers biological control 2-channel

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Protecting Multiple Types of Privacy Simultaneously in EEG-based Brain-Computer Interfaces

arXiv

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arXiv 2024年

作者： Meng, Lubin Jiang, Xue Jia, Tianwang Wu, Dongrui Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

A brain-computer interface (BCI) enables direct communication between the brain and an external device. Electroencephalogram (EEG) is the preferred input signal in non-invasive BCIs, due to its convenience and low cost. EEG-based BCIs have been successfully used in many applications, such as neurological rehabilitation, text input, games, and so on. However, EEG signals inherently carry rich personal information, necessitating privacy protection. This paper demonstrates that multiple types of private information (user identity, gender, and BCI-experience) can be easily inferred from EEG data, imposing a serious privacy threat to BCIs. To address this issue, we design perturbations to convert the original EEG data into privacy-protected EEG data, which conceal the private information while maintaining the primary BCI task performance. Experimental results demonstrated that the privacy-protected EEG data can significantly reduce the classification accuracy of user identity, gender and BCI-experience, but almost do not affect at all the classification accuracy of the primary BCI task, enabling user privacy protection in EEG-based BCIs. © 2024, CC BY.

关键词： Differential privacy

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