IEEE Transactions on Cybernetics最新文献_第2页

AdamGraph: Adaptive Attention-Modulated Graph Network for EEG Emotion Recognition

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-28 DOI: 10.1109/tcyb.2025.3550191

C. L. Philip Chen, Bianna Chen, Tong Zhang

引用次数: 0

Model-Free Algorithms for Cooperative Output Regulation of Discrete-Time Multiagent Systems via Q-Learning Method

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-28 DOI: 10.1109/tcyb.2025.3549821

Huaguang Zhang, Tianbiao Wang, Dazhong Ma, Lulu Zhang

引用次数: 0

Balancing State Exploration and Skill Diversity in Unsupervised Skill Discovery

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-27 DOI: 10.1109/tcyb.2025.3548821

Xin Liu, Yaran Chen, Guixing Chen, Haoran Li, Dongbin Zhao

引用次数: 0

A Sliding Mode Control Method With Variable Convergence Rate for Nonlinear Impulsive Stochastic Systems. 针对非线性脉冲随机系统的可变收敛率滑模控制法

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-27 DOI: 10.1109/TCYB.2025.3551668

Penghe He, Huasheng Zhang, Shun-Feng Su

{"title":"A Sliding Mode Control Method With Variable Convergence Rate for Nonlinear Impulsive Stochastic Systems.","authors":"Penghe He, Huasheng Zhang, Shun-Feng Su","doi":"10.1109/TCYB.2025.3551668","DOIUrl":"https://doi.org/10.1109/TCYB.2025.3551668","url":null,"abstract":"This article addresses the variable convergence rate stability problem for nonlinear impulsive stochastic systems (NISSs). To solve the issue, a novel methodology of sliding mode surface design is presented by combining the definition of interval stability with the T-S fuzzy technique. A pioneering class of sliding mode controllers is constructed in accordance with the characteristics of the designed sliding mode surfaces and the sigmoid function. These controllers can intelligently adjust the convergence rate of the system according to practical requirements, thereby addressing the limitation of fixed convergence rate in existing results. Moreover, the proposed controllers can effectively suppress jitter and analyze the effects of different sigmoid functions on jitter suppression. Sufficient conditions are derived to ensure that the states of the NISSs reach the designed surfaces in finite time and to achieve variable convergence rate stability. The excellent performance of the proposed theoretical strategy in achieving adjustable rate convergence of the system is demonstrated through a simulation of the ball-beam system.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143729913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Privacy for Switched Systems Under MPC: A Privacy-Preserved Rolling Optimization Strategy

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-27 DOI: 10.1109/tcyb.2025.3549063

Yiwen Qi, Shitong Guo, Choon Ki Ahn, Yiwen Tang, Jie Huang

引用次数: 0

Groupwise Label Enhancement Broad Learning System for Image Classification

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-27 DOI: 10.1109/tcyb.2025.3550175

Junwei Jin, Shaokai Chang, Junwei Duan, Yanting Li, Weiping Ding, Zhen Wang, C. L. Philip Chen, Peng Li

引用次数: 0

Z-Number Generation Model and Its Application in a Rule-Based Classification System.

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-25 DOI: 10.1109/TCYB.2025.3545195

Yangxue Li, Juan Antonio Morente-Molinera, Jose Ramon Trillo, Enrique Herrera-Viedma

{"title":"Z-Number Generation Model and Its Application in a Rule-Based Classification System.","authors":"Yangxue Li, Juan Antonio Morente-Molinera, Jose Ramon Trillo, Enrique Herrera-Viedma","doi":"10.1109/TCYB.2025.3545195","DOIUrl":"10.1109/TCYB.2025.3545195","url":null,"abstract":"Due to their unique structure and powerful capability to handle uncertainty and partial reliability of information, Z-numbers have achieved significant success in various fields. Zadeh previously asserted that a Z-number can be regarded as a summary of probability distributions. Researchers have proposed various methods for determining the underlying probability distributions from a given Z-number. Conversely, can a Z-number be used to summarize a set of probability distributions? This problem remains unexplored. In this article, we propose a nonlinear model, termed Maximum Expected Minimum Entropy (MEME), for generating a Z-number from a set of probability distributions. Through this model, Z-numbers can be generated directly from data without requiring expert knowledge. Additionally, we applied the MEME model to classification problems, introducing a novel if-then rule form, termed Z-valuation if-then rules. These rules replace the deterministic consequent part of a fuzzy rule with an uncertain Z-valuation, thereby further summarizing the uncertain information in the rule's consequent. Based on the Z-valuation rules, we propose a Z-valuation rule-based (ZVRB) classification system, which aims to enhance decision-making processes in scenarios where uncertainty plays a key role. To validate the effectiveness of the ZVRB classification system, we conducted two experiments comparing it with both classic and advanced nonfuzzy classifiers as well as fuzzy classification systems. The results show that the ZVRB model is superior to the other comparative classifiers in terms of classification performance.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143709337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-25 DOI: 10.1109/TCYB.2025.3549583

Bin Lu, Fuwang Wang, Junxiang Chen, Guilin Wen, Changchun Hua, Rongrong Fu

{"title":"Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.","authors":"Bin Lu, Fuwang Wang, Junxiang Chen, Guilin Wen, Changchun Hua, Rongrong Fu","doi":"10.1109/TCYB.2025.3549583","DOIUrl":"https://doi.org/10.1109/TCYB.2025.3549583","url":null,"abstract":"The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial features, neglecting valuable local information, potentially leading to suboptimal performance. Therefore, this study proposed a dynamic hierarchical convolutional attention network (DH-CAN) that comprehensively learned discriminative information from both global and local spatial domains, as well as from time-frequency domains in EEG signals. Specifically, a multiscale convolutional block was designed to dynamically capture time-frequency information. The channels of EEG signals were mapped to different brain regions based on motor imagery neural activity patterns. The spatial features, both global and local, were then hierarchically extracted to fully exploit the discriminative information. Furthermore, regional connectivity was established using a graph attention network, incorporating it into the local spatial features. Particularly, this study shared network parameters between symmetrical brain regions to better capture asymmetrical motor imagery patterns. Finally, the learned multilevel features were integrated through a high-level fusion layer. Extensive experimental results on two datasets demonstrated that the proposed model performed excellently across multiple evaluation metrics, exceeding existing benchmark methods. These findings suggested that the proposed model offered a novel perspective for EEG decoding research.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143709324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improved Safe Tracking Error-Constrained Control for Unknown Interconnected Time-Delay Nonlinear Systems With Discontinuous References.

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-25 DOI: 10.1109/TCYB.2025.3548610

Lingchen Zhu, Liuliu Zhang, Cheng Qian, Changchun Hua

{"title":"Improved Safe Tracking Error-Constrained Control for Unknown Interconnected Time-Delay Nonlinear Systems With Discontinuous References.","authors":"Lingchen Zhu, Liuliu Zhang, Cheng Qian, Changchun Hua","doi":"10.1109/TCYB.2025.3548610","DOIUrl":"https://doi.org/10.1109/TCYB.2025.3548610","url":null,"abstract":"In this article, we address the improved error-constrained control problem for unknown, strongly interconnected time-delay nonlinear systems with input saturation and conflicted output constraints. The further challenge we face is that the presence of discontinuous reference signals poses greater difficulties for control design. To tackle these issues, a mechanism for generating smooth, safe reference signals is first devised. Additionally, we propose a novel approach that utilizes improved prescribed performance functions to confine tracking errors within predetermined constant bounds in finite time, while avoiding potential singularity issues arising from abrupt changes in the reference signal. Furthermore, a decentralized adaptive learning error-constrained control strategy is proposed, employing neural networks to approximate complex uncertainties with an asymptotic dynamic surface control method. Stability analysis confirms that the proposed control scheme guarantees the asymptotic stability of the system and ensures safe tracking within conflicted irregular output constraints, even in the presence of input saturation. Finally, simulation results demonstrate the efficacy of the presented control strategy.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143709329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains.

IF 9.4 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-03-25 DOI: 10.1109/TCYB.2025.3550746

Weixiong Yang, Zhijun Li, Guoxin Li, Liangrui Xu

{"title":"Multicontact Safety-Critical Planning and Adaptive Neural Control of a Soft Exosuit Over Different Terrains.","authors":"Weixiong Yang, Zhijun Li, Guoxin Li, Liangrui Xu","doi":"10.1109/TCYB.2025.3550746","DOIUrl":"10.1109/TCYB.2025.3550746","url":null,"abstract":"Many previous works on wearable soft exosuits have primarily focused on assisting human motion, while overlooking safety concerns during movement. This article introduces a novel single-motor, altering bi-directional transfer soft exosuit based on impedance optimization and adaptive neural control, which provides assistance to the lower limbs using Bowden cables. This innovative soft exosuit integrates control barrier functions into the impedance optimization, allowing multiple safety constraints to be considered simultaneously, enabling the system to adaptively learn the impedance of the human ankle joint by analyzing the measured interaction forces at the ankle joint, so that the updated reference trajectories comply with safety requirements. To effectively track the updated reference trajectories, we have introduced an adaptive neural controller based on the integral barrier Lyapunov function. This controller is designed to perform the control task under strict safety constraints. The stability of this control approach is meticulously demonstrated through extensive Lyapunov analysis. In contrast to traditional soft exosuits designed purely for assistance, the key advantage of this technology is its ability to adapt to different terrains while ensuring the safety of human movement during assistance. Through experimental testing, we obtain average tracking errors of 0.0062, 0.0062, and 0.0063 rad for flat, grass, and gravel surfaces, respectively, demonstrating the effectiveness of the proposed strategy.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":9.4,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143709404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0