检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Li, Siyang Wang, Hongbin Chen, Xiaoqing Wu, Dongrui 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 Henan Key Laboratory of Brain Science and Brain Computer Interface Technology School of Electrical and Information Engineering Zhengzhou University China

Brain-computer interfaces (BCIs) enable direct communication between the brain and external devices. This review highlights the core decoding algorithms that enable multimodal BCIs, including a dissection of the elements, a unified view of diversified approaches, and a comprehensive analysis of the present state of the field. We emphasize algorithmic advancements in cross-modality mapping, sequential modeling, besides classic multi-modality fusion, illustrating how these novel AI approaches enhance decoding of brain data. The current literature of BCI applications on visual, speech, and affective decoding are comprehensively explored. Looking forward, we draw attention on the impact of emerging architectures like multimodal Transformers, and discuss challenges such as brain data heterogeneity and common errors. This review also serves as a bridge in this interdisciplinary field for experts with neuroscience background and experts that study AI, aiming to provide a comprehensive understanding for AI-powered multimodal BCIs. © 2025, CC BY-NC-ND.

关键词： Brain computer interface

来源：评论

学校读者我要写书评

暂无评论

Resilience-promoting day-ahead schedule in coastal integrated energy system considering subjective uncertainty

引用

Energy 2025年 328卷

作者： Yu, De-Qi Xiao, Jiang-Wen Wang, Yan-Wu School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education Wuhan 430074 China

This paper studies the resilience enhancement of the energy and water supply in coastal multi-energy system under extreme weather events. A resilience-promoting day-ahead scheduling model is proposed for coastal integrated power-gas-water system under windstorms. Energy coupling and fragility curves related to wind speed are applied into the proposed model to improve system resilience. Specially, subjective uncertainties of operators are described by the mental accounting theory to address the impact of operators’ subjective perceptions on decision analysis, and to enhance psychological satisfaction of operators. The alternating direction method of multipliers algorithm with alternating optimization procedure is employed to obtain a feasible solution for the proposed model while preserving customer privacy. Case studies validate the effectiveness of the proposed model and method by comparative tests. © 2025 Elsevier Ltd

关键词： Day-ahead schedule Integrated power-gas-water system Mental accounting theory Resilience

来源：评论

学校读者我要写书评

暂无评论

Revisiting Euclidean Alignment for Transfer Learning in EEG-Based Brain-Computer Interfaces

arXiv

引用

arXiv 2025年

作者： Wu, Dongrui Ministry of Education Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China

Due to the non-stationarity and large individual differences of EEG signals, EEG-based brain-computer interfaces (BCIs) usually need subject-specific calibration to tailor the decoding algorithm for each new subject, which is time-consuming and user-unfriendly, hindering their real-world applications. Transfer learning (TL) has been extensively used to expedite the calibration, by making use of EEG data from other subjects/sessions. An important consideration in TL for EEG-based BCIs is to reduce the data distribution discrepancies among different subjects/session, to avoid negative transfer. Euclidean alignment (EA) was proposed in 2020 to address this challenge. Numerous experiments from 10 different BCI paradigms demonstrated its effectiveness and efficiency. This paper revisits the EA, explaining its procedure and correct usage, introducing its applications and extensions, and pointing out potential new research directions. It should be very helpful to BCI researchers, especially those who are working on EEG signal decoding. © 2025, CC BY.

关键词： Calibration

来源：评论

学校读者我要写书评

暂无评论

CMCRD: Cross-Modal Contrastive Representation Distillation for Emotion Recognition

arXiv

引用

arXiv 2025年

作者： Kan, Siyuan Wu, Huanyu Cui, Zhenyao Huang, Fan Xu, Xiaolong Wu, Dongrui Key Laboratory of Image Processing and Intelligent Control Ministry of Education School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Wuhan Institute of Digital Engineering Wuhan430074 China Shanghai Jiao Tong University Shanghai200240 China

Emotion recognition is an important component of affective computing, and also human-machine interaction. Unimodal emotion recognition is convenient, but the accuracy may not be high enough;on the contrary, multi-modal emotion recognition may be more accurate, but it also increases the complexity and cost of the data collection system. This paper considers cross-modal emotion recognition, i.e., using both electroencephalography (EEG) and eye movement in training, but only EEG or eye movement in test. We propose cross-modal contrastive representation distillation (CMCRD), which uses a pre-trained eye movement classification model to assist the training of an EEG classification model, improving feature extraction from EEG signals, or vice versa. During test, only EEG signals (or eye movement signals) are acquired, eliminating the need for multi-modal data. CMCRD not only improves the emotion recognition accuracy, but also makes the system more simplified and practical. Experiments using three different neural network architectures on three multi-modal emotion recognition datasets demonstrated the effectiveness of CMCRD. Compared with the EEG-only model, it improved the average classification accuracy by about 6.2%. © 2025, CC BY.

关键词： Modal analysis

来源：评论

学校读者我要写书评

暂无评论

Finite-time sliding-mode control for semi-Markov systems with delayed impulses

引用

IEEE/CAA Journal of Automatica Sinica 2025年

作者： Ren, Fangmin Wang, Xiaoping Li, Yangmin Zeng, Zhigang The School of Artificial Intelligence and Automation The Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Hubei Key Laboratory of Braininspired Intelligent Systems Huazhong University of Science and Technology Wuhan430074 China The Department of Industrial and Systems Engineering The Hong Kong Polytechnic University Hong Kong999077 Hong Kong

来源：评论

学校读者我要写书评

暂无评论

Generation Maintenance Scheduling for Power Systems Considering the Risk Quantification of Hybrid Uncertainty

引用

IEEE Transactions on Power Systems 2025年

作者： Yang, Xiao Zhao, Yong Li, Yuanzheng Huang, Cheng Ding, Qiang Key Laboratory of Image Information Processing and Intelligent Control of Ministry of Education of China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan430074 China Power Science Research Institute of State Grid Jiangsu Electric Power Company China China Electric Power Research Institute Company China

The accurate quantification of risk caused by uncertainty forms a crucial foundation for formulating the generation maintenance scheduling (GMS) of power systems. However, the probability distribution functions (PDFs) of uncertain variables such as wind power and load are challenging to model accurately or are unknown, which makes it difficult to measure their economic risk and formulate appropriate GMS for power systems. To address this issue, we consider hybrid uncertainty from wind power and load, and propose a novel interval-probabilistic worst conditional value-at-risk (IP-WCVaR)-based generation maintenance scheduling method. Firstly, a novel IP-WCVaR method is proposed to measure the risk of the interval and probabilistic hybrid uncertainty, and the analytical mathematical model of the IP-WCVaR is derived through typical scenarios of probability correction. On this basis, the positive and negative spinning reserve models are established using the IP-WCVaR and then integrated into the GMS model, which enhances the resilience of the power system. Finally, the new risk-averse GMS model is formulated as the lower and upper boundary optimal models, which are transformed into tractable mixed integer linear programming problems based on the interval extreme value theory. The effectiveness and superiority of the proposed IP-WCVaR method are verified on the modified IEEE 24-bus and IEEE 118-bus power systems. © 1969-2012 IEEE.

关键词： Mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Hierarchical finite-time optimization regulation of multiple autonomous surface vehicles for time-varying target cooperative tracking

引用

Kongzhi yu Juece/control and Decision 2025年第1期40卷 279-284页

作者： Ge, Ming-Feng Li, Yi-Fan Liu, Zhi-Wei Gu, Zhi-Wei Chen, Qian School of Mechanical Engineering and Electronic Information China University of Geosciences Wuhan430074 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Imaging Processing and Intelligent Control Ministry of Education Huazhong University of Science and Technology Wuhan430074 China

We propose a novel hierarchical finite-time optimization regulation algorithm for multiple autonomous surface vehicles (ASVs) to achieve cooperative tracking of a time-varying target. An objective function reflecting the energy consumption of the multiple ASVs system in the tracking process is designed, and a finite-time optimal estimator (FTOE) is developed to minimize the objective function in the case that ASVs form a specified formation while following the desired trajectory. Meanwhile, the target trajectory can be variable instead of constant. In the finite-time local controller (FTLC), the sailing states of the multiple ASVs system can be stabilized to the vicinity of the multiple various predefined time-varying trajectories in finite time in a way that minimizes the objective function by tracking the FTOE. The proof of the finite-time stability is provided and the settling time is calculated. Finally, simulation results demonstrate the effectiveness of the proposed hierarchical algorithm. © 2025 Northeast University. All rights reserved.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

TSPT: Two-Step Prompt Tuning for class-incremental novel class discovery

引用

Knowledge-Based Systems 2025年 319卷

作者： An, Jiayu Du, Zhenbang Zhang, Herui 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 Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518063 China

In real-world applications, models often encounter a sequence of unlabeled new tasks, each containing unknown classes. This paper explores class-incremental novel class discovery (class-iNCD), which requires maintaining previously learned knowledge while discovering novel classes. We consider a more realistic and also more challenging scenario, which has a small number of initial known classes and a large number of unlabeled tasks, with the additional requirement of data privacy protection. A simple yet effective approach, Two-Step Prompt Tuning (TSPT), is proposed. TSPT tackles class-iNCD through prompt tuning, which is rehearsal-free and plug-and-play, protecting data privacy and significantly reducing the number of trainable parameters. TSPT consists of two main steps: (1) novel class discovery, which initializes the classifier using uniform clustering, and uses intra- and inter-sample consistency learning to discover novel classes;and, (2) knowledge fusion, where the prompt learned in the previous step is adapted as task-specific prompt, and additional optimal prompts are selected from a prompt pool to integrate knowledge from both old and new classes. Experiments on three datasets demonstrated the effectiveness of TSPT. © 2025 Elsevier B.V.

关键词： Sensitive data

来源：评论

学校读者我要写书评

暂无评论

Secure Consensus of Multi-agent Systems via Fully Distributed Dynamic Edge-based Event Triggered Under Denial-of-service Attacks

引用

International Journal of control, Automation and Systems 2025年第5期23卷 1337-1355页

作者： Li, Lei Liu, Lei Yan, Dongmei Liang, Chengqing School of Mathematics Hohai University Nanjing 211100 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 China School of Modern Posts Nanjing University of Posts and Telecommunications Nanjing 210003 China College of Artificial Intelligence and Automation Hohai University Changzhou 213200 China Key Laboratory of Maritime Intelligent Cyberspace Technology Hohai University Ministry of Education Nanjing 210000 China

This paper addresses the issue of ensuring secure consensus in linear multi-agent systems under Denial-of-Service attacks. At the outset, to address the issue of partially observable agent states, a state observer is engineered to offer state estimations for the agents. Using the capabilities of this observer, a novel fully distributed dynamic adaptive edge-based event triggered control mechanism is introduced, and a timing variable is utilized to ensure that the inter-event intervals for all communication links in the network are strictly positive, thereby excluding Zeno behavior. Following that, by leveraging the piecewise Lyapunov function approach, the necessary conditions are meticulously crafted to ensure that the system reaches a secure consensus, thereby establishing a quantitative link between control gains, the duration of attacks, and their frequencies. Ultimately, the effectiveness of the developed event-triggered control strategy is validated through a simulation example. © ICROS, KIEE and Springer 2025.

关键词： Denial-of-service attacks edge-based event triggered control multi-agent systems observer positive minimum interevent time secure consensus

来源：评论

学校读者我要写书评

暂无评论

Surrogate-Assisted Multiobjective Gene Selection for Cell Classification from Large-Scale Single-Cell RNA Sequencing Data

引用

IEEE Transactions on Evolutionary Computation 2025年第3期29卷 601-615页

作者： Lin, Jianqing He, Cheng Jiang, Hanjing Huang, Yabing Jin, Yaochu Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Wuhan430074 China Huazhong University of Science and Technology State Key Laboratory of Advanced Electromagnetic Technology School of Electrical and Electronic Engineering Wuhan430074 China Renmin Hospital Department of Pathology Wuhan University Wuhan430060 China Westlake University Trustworth and General Artificial Intelligence Laboratory School of Engineering Hangzhou310030 China

Accurate cell classification is crucial but expensive for large-scale single-cell RNA sequencing (scRNA-seq) analysis. Gene selection (GS) emerges as a pivotal technique in identifying gene subsets of scRNA-seq for classification accuracy improvement and gene scale reduction. Nevertheless, the rising scale of scRNA-seq data presents challenges to existing GS methods regarding performance and computational time. Thus, we propose a surrogate-assisted evolutionary algorithm for multiobjective GS to address these deficiencies. An innovative two-phase initialization method is proposed to select sparse solutions to provide preliminary insights into gene contributions. Then, a binary competitive swarm optimizer is proposed for effective global search, where a local search method is embedded to eliminate irrelevant genes for efficiency consideration. Additionally, a surrogate model is adopted to forecast classification accuracy efficiently and substitutes part of the computationally expensive classification process. Experiments are conducted on eight large-scale scRNA-seq datasets with more than 20,000 genes. The effectiveness of the proposed GS method for scRNA-seq cell classification compared with eight state-of-the-art methods is validated. Gene expression analysis results of selected genes further validated the significance of the genes selected by the proposed method in the classification of scRNA-seq data. © 1997-2012 IEEE.

关键词： Gene expression

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：