IEEE Transactions on Cybernetics最新文献_第8页

Secure Tracking Control of Cyber-Physical Systems Against Hybrid Attacks via FAS Terminal Sliding-Mode Predictive Control 基于FAS终端滑模预测控制的信息物理系统抗混合攻击安全跟踪控制

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-28 DOI: 10.1109/tcyb.2025.3569664

Da-Wei Zhang, Guo-Ping Liu

引用次数: 0

Low-Complexity Distributed Prescribed Performance Control of Unknown Nonlinear Multiagent Systems Under Switching Topologies 切换拓扑下未知非线性多智能体系统的低复杂度分布式预定性能控制

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-26 DOI: 10.1109/tcyb.2025.3569418

Hai-Xiu Xie, Jin-Xi Zhang, Tianyou Chai

引用次数: 0

An Interpretable Quantum Adjoint Convolutional Layer for Image Classification. 一种用于图像分类的可解释量子伴随卷积层。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-22 DOI: 10.1109/tcyb.2025.3567090

Shi Wang,Mengyi Wang,Ren-Xin Zhao,Licheng Liu,Yaonan Wang

{"title":"An Interpretable Quantum Adjoint Convolutional Layer for Image Classification.","authors":"Shi Wang,Mengyi Wang,Ren-Xin Zhao,Licheng Liu,Yaonan Wang","doi":"10.1109/tcyb.2025.3567090","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3567090","url":null,"abstract":"The interpretability of quantum machine learning (QML) refers to the capability to provide clear and understandable explanations for the predictions and decision-making processes of QML models. However, most quantum convolutional layers (QCLs) utilize closed-box structures that are inherently devoid of interpretability, leading to the opacity of principles and the suboptimal mapping of classical data. This significantly undermines the reliability of QML models. In addition, most of the current QML interpretability focuses on post hoc interpretability seriously neglecting the importance of exploring intrinsic causes. To tackle these challenges, we introduce the quantum adjoint convolution operation (QACO). It is an intrinsic interpretability scheme based on quantum evolution, as its quantum mapping precisely corresponds to the position and pixel values of the image and its principle is equivalent to the Frobenius inner product (FIP). Furthermore, we extend the QACO concept into the quantum adjoint convolutional layer (QACL) by integrating the quantum phase estimation (QPE) algorithm, enabling the parallel computation of all FIPs. Experimental results on PennyLane and TensorFlow platforms demonstrate that our method achieves a 6.3%, 3.4%, and 2.9% higher average test accuracy on Fashion MNIST, MNIST, and DermaMNIST datasets compared to classical and uninterpretable quantum counterparts, respectively, while maintaining 73.3% noise-robust accuracy under Gaussian noise, showcasing its superior generalizability and resilience in practical scenarios.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"31 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144122165","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

Resilient Collision-Free Distributed Optimal Coordination for Multiple Euler-Lagrangian Systems Under Unreliable Communication Topologies. 不可靠通信拓扑下多欧拉-拉格朗日系统弹性无碰撞分布式最优协调。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-20 DOI: 10.1109/tcyb.2025.3566155

Jia-Yuan Yin,Guang-Hong Yang,Huimin Wang

引用次数: 0

Piecewise Constant Tuning Gain-Based Singularity-Free MRAC With Application to Aircraft Control Systems 基于分段恒整定增益的无奇异MRAC在飞机控制系统中的应用

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-19 DOI: 10.1109/tcyb.2025.3567177

Zhipeng Zhang, Yanjun Zhang, Jian Sun

引用次数: 0

Decentralized Adaptive Secure Control of Nonlinear NCSs Under Hybrid Attacks via Event-Triggering 基于事件触发的混合攻击下非线性ncs分散自适应安全控制

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-14 DOI: 10.1109/tcyb.2025.3567457

Weiwei Sun, Lusong Ding, Yongshu Li, Dehai Yu

引用次数: 0

Self-Adjustable and Flexible Performance-Based Event-Triggered Asymptotic Tracking Control of Nonlinear Systems With Unknown Control Directions 未知控制方向非线性系统基于性能的自调柔性事件触发渐近跟踪控制

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-09 DOI: 10.1109/tcyb.2025.3563585

Haibin Sun, Xiangling Kong, Jun Yang, Linlin Hou, Dong Yang

引用次数: 0

Discrete Memristive Conservative Chaotic Map: Dynamics, Hardware Implementation, and Application in Secure Communication. 离散记忆保守混沌映射：动力学、硬件实现和在安全通信中的应用。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-08 DOI: 10.1109/tcyb.2025.3565333

Quanli Deng,Chunhua Wang,Yichuang Sun,Gang Yang

{"title":"Discrete Memristive Conservative Chaotic Map: Dynamics, Hardware Implementation, and Application in Secure Communication.","authors":"Quanli Deng,Chunhua Wang,Yichuang Sun,Gang Yang","doi":"10.1109/tcyb.2025.3565333","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3565333","url":null,"abstract":"The randomness of chaotic systems are crucial for their application in secure communication. Conservative systems exhibit enhanced ergodicity and randomness in comparison to dissipative chaotic systems. However, the memristor-based conservative chaotic maps remain unreported. This article presents a study of volume-preserving chaotic maps based on discrete memristor (DM). We propose and analyze a generic conservative map that incorporates DM. The conservative characteristics of the proposed iterative map are confirmed through the determinant of its Jacobian matrix. Furthermore, four distinct DM models are introduced and their memristive characteristics are verified through numerical simulations of hysteresis loops. To investigate the dynamical properties of the discrete memristive conservative map (DMCM), we incorporate the proposed DM models into the generic conservative map model using numerical methods, including phase portraits, Lyapunov exponents, and bifurcation diagrams. Additionally, the hardware implementation of the DMCM on an FPGA platform demonstrates the reliability of the model. Finally, secure communication experiments based on the DMCM show that it outperforms some classical dissipative chaotic maps in terms of bit error rate performance.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"120 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143926524","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

Robust Multiobjective Competitive Swarm Optimization Based on Evolutionary Trend Prediction. 基于进化趋势预测的鲁棒多目标竞争群优化。

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-08 DOI: 10.1109/tcyb.2025.3565010

Honggui Han,Hao Zhou,Yanting Huang,Ying Hou

{"title":"Robust Multiobjective Competitive Swarm Optimization Based on Evolutionary Trend Prediction.","authors":"Honggui Han,Hao Zhou,Yanting Huang,Ying Hou","doi":"10.1109/tcyb.2025.3565010","DOIUrl":"https://doi.org/10.1109/tcyb.2025.3565010","url":null,"abstract":"The competitive swarm optimizer (CSO) has been widely used for addressing multiobjective optimization problems owing to its diverse learning approach. However, the evolutionary process uncertainty within the algorithm weakens the optimization reliability. To deal with this concern, a robust multiobjective CSO with a predictive indicator (RMOCSO-PI), is proposed. This approach can reduce aimless and inefficient searches caused by the uncertainty to enhance algorithmic robustness. First, a predictive indicator is established based on the autoregressive model, which utilizes historical swarm distribution data to predict the evolutionary trends. Then, the particles are classified into winners and losers by evaluating their evolutionary potential, whose evolution would be guided differentially. Second, a space fusion-based competitive mechanism is designed to generate precise evolution directions for loser particles. The space fusion-based adaptive adjustment method integrates the learning cost metric in decision space with the learning worth metric in objective space for proper learning weight settings. Third, a dynamic cooperative mechanism is presented to purposefully guide the diversity exploration of particles. By estimating evolutionary states, three cooperative patterns are dynamically assigned to particles for purposeful diversity exploration. To provide theoretical support for the validity and reliability of RMOCSO-PI, a convergence analysis is given. Furthermore, experimental results verify that RMOCSO-PI has more stable and excellent optimization performance.","PeriodicalId":13112,"journal":{"name":"IEEE Transactions on Cybernetics","volume":"55 1","pages":""},"PeriodicalIF":11.8,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143926526","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

Controllability of Networked Sampled-Data Systems With Time Delays 时滞网络采样数据系统的可控性

IF 11.8 1区计算机科学

IEEE Transactions on Cybernetics Pub Date : 2025-05-02 DOI: 10.1109/tcyb.2025.3562221

Zixuan Yang, Lin Wang, Xiaofan Wang, Guanrong Chen

引用次数: 0