检索结果-内蒙古大学图书馆

14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019

作者： Hu, Yingxin Wang, Zhiyu Chen, Zhekun Liao, Sulin Huang, Yabing Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology WuhanHubei430074 China College of Information Science and Technology Shijiazhuang Tiedao University ShijiazhuangHebei050043 China School of Computer Science and Technology Huazhong University of Science and Technology WuhanHubei430074 China Department of Pathology Renmin Hospital of Wuhan University WuhanHubei430060 China

ISBN: (纸本)9789811534140

Molecular carch hotspots in the area of DNA nanotechnology due to its inherent large storage capacity, high parallelism, and energy efficiency. The assembled structures in the existing computing units mainly adopt a double-helix structure. However, besides duplex, DNA is known to adopt other helical forms such as triplex form. The triplex structure has introduced a novel paradigm into the DNA engineer owing to their unique characteristic sequence, structural and assembly requirements. Based on the assembly and disassembly of the triplex structure, a YES logic gate was constructed via strand displacement reaction. The experiment results showed that GC content and stem length would influence the displacement reaction. Then AND logic gate was also established through cooperative effect by two DNA strands. The construction of the cascading circuit indicated triplex-based logic gate could be integrated into larger circuits and enrich the toolbox of the computing devices. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Logic gates

来源：评论

学校读者我要写书评

暂无评论

A memristor-based generalization and differentiation circuit design and the application in recognition

A memristor-based generalization and differentiation circuit...

引用

Chinese control Conference (CCC)

作者： Meijia Shang Xiaoping Wang Mian Li School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Artificial Intelligence and Automation Huazhong University of Science and Technology and also with the Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

The traditional Pavlov associative memory circuit realizes the law of learning and forgetting in classical conditioned reflex. In addition, the law of generalization and differentiation also belongs to classical conditioned reflex, so the process of associative memory can be more effectively simulated by adding generalization and differentiation theory on the basis of traditional associative memory. In this paper, a memristor-based circuit is designed to implement generalization and differentiation based on Pavlov associative memory. The circuit can be applied to simple classification recognition. Based on the features of objects as input, the output of the circuit is used as the classification result to achieve the function of classification and recognition. Finally, the accuracy of classification recognition on the generalization and differentiation circuit proposed in this paper can be verified by the simulation results in PSPICE.

关键词： Neurons Threshold voltage Associative memory Dogs Memristors Logic gates Circuit synthesis

来源：评论

学校读者我要写书评

暂无评论

Supervised Enhanced Soft Subspace Clustering (SESSC) for TSK Fuzzy Classifiers

arXiv

引用

arXiv 2020年

作者： Cui, Yuqi Wang, Huidong Wu, Dongrui Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Management Science and Engineering Shandong University of Finance and Economics Jinan250014 China

Fuzzy c-means based clustering algorithms are frequently used for Takagi-Sugeno-Kang (TSK) fuzzy classifier antecedent parameter estimation. One rule is initialized from each cluster. However, most of these clustering algorithms are unsupervised, which waste valuable label information in the training data. This paper proposes a supervised enhanced soft subspace clustering (SESSC) algorithm, which considers simultaneously the within-cluster compactness, between-cluster separation, and label information in clustering. It can effectively deal with high-dimensional data, be used as a classifier alone, or be integrated into a TSK fuzzy classifier to further improve its performance. Experiments on nine UCI datasets from various application domains demonstrated that SESSC based initialization outperformed other clustering approaches, especially when the number of rules is small. Copyright © 2020, The Authors. All rights reserved.

关键词： Fuzzy clustering

来源：评论

学校读者我要写书评

暂无评论

Transfer Learning for EEG-Based Brain-Computer Interfaces: A Review of Progress Made Since 2016

arXiv

引用

arXiv 2020年

作者： Wu, Dongrui Xu, Yifan Lu, Bao-Liang The Ministry of Education Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Brain Science and Technology Research Center Qing Yuan Research Institute Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai200240 China

A brain-computer interface (BCI) enables a user to communicate with a computer directly using brain signals. The most common non-invasive BCI modality, electroencephalogram (EEG), is sensitive to noise/artifact and suffers between-subject/within-subject non-stationarity. Therefore, it is difficult to build a generic pattern recognition model in an EEG-based BCI system that is optimal for different subjects, during different sessions, for different devices and tasks. Usually, a calibration session is needed to collect some training data for a new subject, which is time-consuming and user unfriendly. Transfer learning (TL), which utilizes data or knowledge from similar or relevant subjects/sessions/devices/tasks to facilitate learning for a new subject/session/device/task, is frequently used to reduce the amount of calibration effort. This paper reviews journal publications on TL approaches in EEG-based BCIs in the last few years, i.e., since 2016. Six paradigms and applications - motor imagery, event-related potentials, steady-state visual evoked potentials, affective BCIs, regression problems, and adversarial attacks - are considered. For each paradigm/application, we group the TL approaches into cross-subject/session, cross-device, and cross-task settings and review them separately. Observations and conclusions are made at the end of the paper, which may point to future research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

Fault Detection of Lithium-Ion Batteries Subject to Probabilistic Parametric Uncertainties

Fault Detection of Lithium-Ion Batteries Subject to Probabil...

引用

Fault Detection, Supervision and Safety for Technical Processes (SAFEPROCESS), CAA Symposium on

作者： Yuhao Liu Yiming Wan Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan China

ISBN: (数字)9781728106816

ISBN: (纸本)9781728106823

The fault detection task in lithium-ion battery management system (BMS) is critical to the safety and reliability of rechargeable and hybrid electric vehicles. To explicitly account for inevitable errors of battery model parameters, a robust fault detection method is proposed in this paper. The residual generator is established by exploiting an equivalent circuit model. The effect of uncertainties on the residual is parametrized as polynomial dependence on probabilistic uncertain parameters and noises. Then Gaussian mixtures are adopted to derive the residual distribution. To account for residual uncertainties in the detection decision, the weighted sum of distances from the generated residual to each Gaussian component of the residual distribution is proposed. Simulation results illustrate that our proposed method outperforms the conventional approach that does not consider parametric uncertainties.

关键词： Uncertainty Batteries Integrated circuit modeling Uncertain systems Voltage measurement Electronic countermeasures State of charge

来源：评论

学校读者我要写书评

暂无评论

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

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

引用

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

来源：评论

学校读者我要写书评

暂无评论

Observer-Based Robust Containment control of Multi-agent Systems With Input Saturation

Observer-Based Robust Containment Control of Multi-agent Sys...

引用

Chinese control Conference (CCC)

作者： Juan Qian Xiaoling Wang Guo-Ping Jiang Housheng Su College of Automation and College of Artificial Intelligence Nanjing University of Posts and Telecommunications and Jiangsu Engineering Lab for IOT Intelligent Robots(IOTRobot) Nanjing PR China School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry ofChina Huazhong University of Science and Technology Wuhan PR China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In this paper, the robust containment control problem of the leader-following multi-agent systems with input saturation and input additive disturbance is addressed, where the followers can be informed by multiple leaders. With the help of the lowand-high gain feedback technique and the high-gain observer approach, a distributed control algorithm for each agent is firstly designed by using the observed output information, then sufficient conditions are provided to guarantee the semi-global robust containment of the system. Finally, some numerical simulations are given to verify the correctness of the theoretical results.

关键词： Multi-agent systems Robustness Observers Electronic mail State feedback Additives

来源：评论

学校读者我要写书评

暂无评论

Deep reinforcement learning with a stage incentive mechanism of dense reward for robotic trajectory planning

arXiv

引用

arXiv 2020年

作者： Peng, Gang Yang, Jin Khyam, Mohammad Omar Key Laboratory of Image Processing and Intelligent Control Ministry of EducationB School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China School of Automation South East University Nanjing China School of Engineering and Technology Central Queensland University Melbourne Australia

To improve the efficiency of deep reinforcement learning (DRL)-based methods for robot manipulator trajectory planning in random working environments, we present three dense reward functions. These rewards differ from the traditional sparse reward. First, a posture reward function is proposed to speed up the learning process with a more reasonable trajectory by modeling the distance and direction constraints, which can reduce the blindness of exploration. Second, a stride reward function is proposed to improve the stability of the learning process by modeling the distance and movement distance of joint constraints. Finally, in order to further improve learning efficiency, we are inspired by the cognitive process of human behavior and propose a stage incentive mechanism, including a hard stage incentive reward function and a soft stage incentive reward function. Extensive experiments show that the soft stage incentive reward function is able to improve the convergence rate by up to 46.9% with the state-of-the-art DRL methods. The percentage increase in the convergence mean reward was 4.4-15.5% and the percentage decreases with respect to standard deviation were 21.9-63.2%. In the evaluation experiments, the success rate of trajectory planning for a robot manipulator reached 99.6%. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Neighborhood Interval Observer Based Coordination control for Multi-agent Systems with Disturbances ⁎

引用

IFAC-PapersOnLine 2020年第2期53卷 10994-10999页

作者： Xiaoling Wang Guo-Ping Jiang Wen Yang Housheng Su Xiaofan Wang College of Automation Nanjing University of Posts and Telecommunications Nanjing 210023 China and also with Jiangsu Engineering Lab for IOT Intelligent Robots (IOTRobot) Nanjing 210023 China Key Laboratory of Advanced Control and Optimization for Chemical Processes East China University of Science and Technology Shanghai 200237 China School of Artifcial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China Department of Automation Shanghai University Shanghai 200072 China

This paper focuses on multi-agent systems with uncertain disturbances, in which only the bounding functions on the disturbances and the bounds on the initial state of each agent are known. By designing a neighborhood interval observer for this kind of multi-agent system, the estimation of the sum of the relative state of each agent associated with itself and its neighbors is frstly realized. Then, on the basis of these estimated information, local control algorithm is designed to drive the system to achieve bounded consensus.

关键词： Multi-agent system disturbance neighborhood interval observer bounded consensus

来源：评论

学校读者我要写书评

暂无评论

control-oriented fault detection of solid oxide fuel cell system unknown input on fuel supply

Control-oriented fault detection of solid oxide fuel cell sy...

引用

作者： Wu, Xiao-long Xu, Yuan-wu Xue, Tao Shuai, Junchao Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Wuhan Industrial Economic Development Research Center Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China

As the solid oxide fuel cell (SOFC) system work environment is a high-temperature environment for a long time, it is difficult to obtain the SOFC stack internal state change directly. When the fault occurs, it is difficult to determine where the fault occurs. Moreover, the existing literature ignores the impact of faults, which creates many problems for SOFC system control. Therefore, a state observer-based fault detection method, which is used to detect the input flow sensor fault and the fuel input fault, is proposed. Their advantage is that they do not need data processing. To realize the fault detection, the observer is used to track the changes of SOFC stack chamber temperature. To obtain the observer estimation parameter, an approach from the actual stack structure parameters is employed to approximate the observer parameters. The results show the proposed fault detect method can judge fuel input fault type quickly and shield the disturbances signals from the sensor effectively. The proposed method also can be used to other operating points or air input fault. © 2018 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Fault detection

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：