IEEE Transactions on Cybernetics最新文献_第10页

Asynchronous Fault-Tolerant Control Against Infinite Cycle Faults With Application to a Space-Borne Digital System 无限循环异步容错控制在星载数字系统中的应用

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-31 DOI: 10.1109/tcyb.2026.3711152

Jung-Min Yang, Seong Woo Kwak

引用次数: 0

DL-Based Reduced-Order Modeling and Fuzzy Output Tracking Control Design With Vibration Suppression for a Flexible Morphing Aircraft 柔性变形飞行器基于dl的降阶建模与模糊输出跟踪控制设计

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-30 DOI: 10.1109/tcyb.2026.3711951

Huai-Ning Wu, Jin-Feng Zhang, Jun-Wei Wang, Jia-Yu Cui

引用次数: 0

A Novel End-to-End Low-Light Image Segmentation Method and Its Application to Robotic Perception. 一种新的端到端弱光图像分割方法及其在机器人感知中的应用。

IF 11.3 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-29 DOI: 10.1109/TCYB.2026.3716034

Zhengcai Cao, Hongmin Mu, MengChu Zhou

{"title":"A Novel End-to-End Low-Light Image Segmentation Method and Its Application to Robotic Perception.","authors":"Zhengcai Cao, Hongmin Mu, MengChu Zhou","doi":"10.1109/TCYB.2026.3716034","DOIUrl":"10.1109/TCYB.2026.3716034","url":null,"abstract":"In the fields of robotic perception and computer vision, achieving accurate semantic segmentation of low-light or nighttime scenes is challenging. This is mainly due to the limited visibility of objects and reduced texture and color contrasts among them. To address the issue of reduced texture among objects, we propose a dual closed-loop bipartite matching algorithm to establish a total loss function consisting of unsupervised illumination enhancement loss and supervised intersection-over-union loss, thus enabling the joint minimization of both losses via the Hungarian algorithm. We can thus achieve end-to-end training for a semantic segmentation network especially suitable for handling low-light scenes. By utilizing reference daylight images of similar scenes, we propose a weakly supervised method with selective refinement to improve segmentation accuracy in underperforming categories, thus resulting in a model with superior performance. Experimental results show that the proposed network surpasses existing methods on the Cityscapes dataset and notably outperforms state-of-the-art methods on Dark Zurich and Nighttime Driving datasets. We finally deploy the proposed model on quadruped robots to evaluate its performance in outdoor low-light scenes, where it demonstrates superior segmentation capabilities over existing real-time semantic segmentation networks.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":11.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148619783","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

Feature Selection Approach Based on Stacked Density Granulation With Principle of Justifiable Granularity. 基于合理粒度原则的堆积密度造粒特征选择方法。

IF 11.3 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-29 DOI: 10.1109/TCYB.2026.3715550

Wentao Li, Xuanzhen Zhao, Witold Pedrycz, Chao Zhang, Tao Zhan

{"title":"Feature Selection Approach Based on Stacked Density Granulation With Principle of Justifiable Granularity.","authors":"Wentao Li, Xuanzhen Zhao, Witold Pedrycz, Chao Zhang, Tao Zhan","doi":"10.1109/TCYB.2026.3715550","DOIUrl":"10.1109/TCYB.2026.3715550","url":null,"abstract":"Information granularity provides a framework for machine intelligence to simulate human cognitive processes in problem-solving, enabling machines to make more flexible and adaptive decisions in complex data environments. However, most existing information granularities are based on fuzzy c-mean (FCM) or K-means clustering for granularity construction. This kind of convex data structure clustering has difficulty in recognizing some irregular nonconvex data types, and can only be filled irregularly by increasing the cluster classes, which is easy to lose the wholeness and accuracy of the data. The density-based spatial clustering of applications with noise (DBSCAN), a classical density-based spatial clustering method, is well-suited for both convex and nonconvex datasets. Building on the versatility of DBSCAN, a new density-based clustering method called stacked density granulation (SDG) is proposed, which constructs information granularities capable of effectively describing both convex and nonconvex data. This approach addresses the limitations of traditional information granularity. By applying the newly constructed information granularities to the feature space, the importance of features can be measured. To enhance this process, a heuristic feature selection method called density granular feature selection (DGFS) is introduced. DGFS constructs a low-dimensional feature space by aggregating and discretizing the information granularities, retaining only the most relevant features. To demonstrate the superiority and effectiveness of the DGFS algorithm, 12 publicly available datasets are utilized, and its performance is compared with other feature selection methods across four different classifiers. The experimental results and the statistical significance test indicate that DGFS consistently outperforms the competing methods.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":11.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148619766","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

Comprehensive Review of Calibration Techniques for Serial Link Manipulators: Insights Into Mathematical and Methodological Evolutions. 对连续连杆机械手校准技术的全面回顾：对数学和方法演变的见解。

IF 11.3 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-29 DOI: 10.1109/TCYB.2026.3712508

Armin Karoly, Huijun Gao, Imre J Rudas, Peter Galambos

引用次数: 0

Retraction Notice: Multiple Transformation Matrix-Based Adaptive Projective Vortex Formation Tracking for Multiagent Systems With a Leader of Completely Unknown Input. 引用本文：具有完全未知输入的多智能体系统的基于多重变换矩阵的自适应投影涡流跟踪。

IF 11.3 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-29 DOI: 10.1109/TCYB.2026.3716178

Xiangyang Du, Jihong Shen, Shujuan Wang

{"title":"Retraction Notice: Multiple Transformation Matrix-Based Adaptive Projective Vortex Formation Tracking for Multiagent Systems With a Leader of Completely Unknown Input.","authors":"Xiangyang Du, Jihong Shen, Shujuan Wang","doi":"10.1109/TCYB.2026.3716178","DOIUrl":"10.1109/TCYB.2026.3716178","url":null,"abstract":"This article systematically studies projective vortex formation tracking (PVFT) of linear multiagent systems (MASs) on directed graphs through multiple transformation matrices, in which the input of leader and its upper bound information are not available to any follower. First, an innovative class of distributed adaptive observer is designed using the projection matrices to capture multiple desired virtual signals of the leader. Next, a novel kind of distributed PVFT protocol based on distributed observer, local observer and coordinates coupling matrices are proposed. Two different adaptive update mechanisms and nonlinear functions are introduced in the observer and controller to override the unknown input of the leader. Then, an algorithm is given, and the protocol under the algorithm is proved from three processes of estimation, aggregation, and rotation to enable linear systems to achieve PVFT. Finally, the effects of parameters on aggregation and rotation are analyzed systematically, and several simulation examples are given to illustrate the reliability of the results.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":11.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148619855","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

SWiST DeepNet: Spectral-Temporal Deep Network for Detecting Resonance-Based Attacks on MEMS Inertial Sensors. SWiST深度网络：用于检测基于共振的MEMS惯性传感器攻击的频谱-时间深度网络。

IF 11.3 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-29 DOI: 10.1109/TCYB.2026.3715653

Chudamani Sahu, Akram Al-Hourani, Sumeet Walia, Shashi Poddar

{"title":"SWiST DeepNet: Spectral-Temporal Deep Network for Detecting Resonance-Based Attacks on MEMS Inertial Sensors.","authors":"Chudamani Sahu, Akram Al-Hourani, Sumeet Walia, Shashi Poddar","doi":"10.1109/TCYB.2026.3715653","DOIUrl":"10.1109/TCYB.2026.3715653","url":null,"abstract":"Microelectromechanical systems (MEMSs)-based inertial sensors, such as accelerometers and gyroscopes, are fundamental to the operation of cyber-physical systems (CPSs), enabling real-time motion tracking and orientation estimation. However, their susceptibility to resonance-based acoustic interference can lead to false measurements, corrupting sensor outputs and potentially destabilizing the systems that rely on them. To detect such threats, this article proposes a sliding-window-based deep learning framework that uses temporal- and spectral-domain features to identify resonance-induced signal injections. The model is evaluated under diverse and realistic operating conditions, including both static and dynamic motion, and across three defined attack levels: soft, medium, and hard. The experimental analysis compares the performance of temporal, spectral, and a fusion of spectral- and temporal-domain features for attack detection across different window lengths. The proposed sliding window spectral-temporal deep network (SWiST DeepNet) architecture reliably detect attacks even at low intensities down to a 10-dB attack-to-signal ratio (ASR), significantly enhancing the resilience and trustworthiness of CPS against resonance-based attacks. Our datasets are available at https://github.com/cmsahu97/RAiS-dataset.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"PP ","pages":""},"PeriodicalIF":11.3,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148619772","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

Secure State Estimation for Systems With Silent Packet Loss and Its Application to Controller Design 具有静默丢包系统的安全状态估计及其在控制器设计中的应用

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-28 DOI: 10.1109/tcyb.2026.3710883

Hong Lin, Shan Lu, Ye Li, Yuman Li, Xiaochen Xie

引用次数: 0

Adaptive Dynamic Programming-Based Optimal Circumnavigation Control of Multi-UAV Systems via Orthogonal Vector Construction in 3-D Space 基于三维空间正交向量构造的自适应动态规划多无人机最优绕航控制

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2026-07-28 DOI: 10.1109/tcyb.2026.3715837

Yanhong Luo, Yannan Li, Qinglai Wei, Dongsheng Yang

引用次数: 0

Optimal Stealthy Attacks With Historical Data in Cyber-Physical Systems Under Periodic Detection 周期检测下网络物理系统历史数据最优隐身攻击