Journal of The Franklin Institute-engineering and Applied Mathematics最新文献_第4页

Distributed adaptive learning consensus tracking control for a class of nonlinear 2-D multi agent systems with nonrepetitive conditions

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-23 DOI: 10.1016/j.jfranklin.2025.107673

Qing-Yuan Xu , Yuan Fang , Mian Guo , Yun-Shan Wei , Kai Wan

{"title":"Distributed adaptive learning consensus tracking control for a class of nonlinear 2-D multi agent systems with nonrepetitive conditions","authors":"Qing-Yuan Xu , Yuan Fang , Mian Guo , Yun-Shan Wei , Kai Wan","doi":"10.1016/j.jfranklin.2025.107673","DOIUrl":"10.1016/j.jfranklin.2025.107673","url":null,"abstract":"<div><div>This study tackles the output consensus problem for a class of nonlinear two-dimensional (2-D) multi agent systems that do complex tasks repetitively in a finite domain via adaptive iterative learning control (ILC). The aim is to design a distributed adaptive learning consensus tracking control strategy that enables all 2-D multi agents to achieve the task of consensus tracking control under nonrepetitive conditions. An adaptive parameter, which adjusted by the tracking errors of the agent itself and the neighbor agents in the last iteration, is designed to approximate the unknown varying parameter of the nonlinear 2-D agent. Then, based on the approximated parameter and the iteration-varying reference surfaces, the distributed adaptive ILC strategy is obtained and the convergence of the output consensus tracking control is proved. In the end, simulations are presented to verify the effectiveness of the proposed distributed adaptive learning consensus tracking control for nonlinear 2-D multi agent system with nonrepetitive conditions.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107673"},"PeriodicalIF":3.7,"publicationDate":"2025-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143760945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Different types of Plancherel’s theorems for square integrable functions associated with quaternion offset linear canonical transforms

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-21 DOI: 10.1016/j.jfranklin.2025.107649

Manab Kundu

引用次数: 0

Reversible Data Hiding for JPEG Images Based on Point Distortion Estimation Optimization

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-21 DOI: 10.1016/j.jfranklin.2025.107657

Li Liu , Kexin Fu , Yingchun Wu , Ching-Chun Chang , Anhong Wang , Chin-Chen Chang

{"title":"Reversible Data Hiding for JPEG Images Based on Point Distortion Estimation Optimization","authors":"Li Liu , Kexin Fu , Yingchun Wu , Ching-Chun Chang , Anhong Wang , Chin-Chen Chang","doi":"10.1016/j.jfranklin.2025.107657","DOIUrl":"10.1016/j.jfranklin.2025.107657","url":null,"abstract":"<div><div>Reversible data hiding (RDH) for joint photographic experts group (JPEG) images has been extensively studied to achieve a perfect balance between image visual quality and file size increment. In this paper, we propose RDH algorithm for JPEG images, optimized through point distortion estimation (PDEO). First, we construct a PDEO model that takes into account block smoothness, quantization step, and zigzag sorting position, and then arrange each AC coefficient in ascending order according to the point distortion estimate, because preferentially embedding in the AC coefficient with less distortion can obtain better image quality. Second, we design the principle of \"pair when ±1 appears\" to makes full use of ±1 coefficients to increase the embedding capacity. Finally, the secret data is embedded into the AC coefficient pairs by using our designed 1D and 2D histogram mapping generation strategy. Experimental results demonstrate that the proposed algorithm offers superior visual image quality compared to other advanced JPEG RDH algorithms, with a smaller increase in file size and a more optimal balance in runtime complexity.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107657"},"PeriodicalIF":3.7,"publicationDate":"2025-03-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143746351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Modified Triplet-Average Deep Deterministic Policy Gradient for interpretable neuro-fuzzy deep reinforcement learning

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-20 DOI: 10.1016/j.jfranklin.2025.107653

Tuan-Linh Nguyen , Nguyen Van Thin , Sangmoon Lee

引用次数: 0

Security control for two-time-scale networked systems under unreliable Markov networks subject to hybrid attacks

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-20 DOI: 10.1016/j.jfranklin.2025.107641

Jingjing Hou, Xiulin Wang, Youzhi Cai, Feng Li, Hao Shen

{"title":"Security control for two-time-scale networked systems under unreliable Markov networks subject to hybrid attacks","authors":"Jingjing Hou, Xiulin Wang, Youzhi Cai, Feng Li, Hao Shen","doi":"10.1016/j.jfranklin.2025.107641","DOIUrl":"10.1016/j.jfranklin.2025.107641","url":null,"abstract":"<div><div>This work addresses the security control problem of two-time-scale networked systems operating on unreliable Markov networks under hybrid attacks. Markov jump processes are employed to model the different types of network attacks that the system may encounter, thereby defining three operational modes: normal operation, deception attacks, and scaling attacks. A non-fragile control strategy is proposed to mitigate gain fluctuations resulting from unexpected errors and disturbances, which can enhance the robustness of the designed controller. A Lyapunov function with singular perturbation parameter is constructed to analyze both the system stability and <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> performance index, where the singular perturbation parameter characterize the dynamics associated with fast and slow time-scale variations, leading to a set of sufficient stability conditions. Finally, the validity of the proposed control method is verified via numerical simulations.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107641"},"PeriodicalIF":3.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Fixed-time precision formation control of multi-AUVs with assured transient performance

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-18 DOI: 10.1016/j.jfranklin.2025.107638

Jianhui Wang , Haoyuan Wang , Yue Zhang , C.L. Philip Chen , Zhi Liu , Chunliang Zhang

{"title":"Fixed-time precision formation control of multi-AUVs with assured transient performance","authors":"Jianhui Wang , Haoyuan Wang , Yue Zhang , C.L. Philip Chen , Zhi Liu , Chunliang Zhang","doi":"10.1016/j.jfranklin.2025.107638","DOIUrl":"10.1016/j.jfranklin.2025.107638","url":null,"abstract":"<div><div>A rapid and stable dimensional augmented state observer (RSDASO), employing an event-driven control strategy, is proposed to tackle the challenges of trajectory-tracking formation control for multiple autonomous underwater vehicles (AUVs). This approach addresses state constraints, unmeasurable states, model uncertainties, limited communication resources, and unknown external time-varying disturbances. The initial phase involves developing a RSDASO to estimate superimposed disturbances and unmeasurable states within the system, ensuring that the estimation error converges within a fixed time. Subsequently, a smoothly decreasing performance function is integrated into the controller design using the observer and an adaptive fixed-time filter. This approach ensures that the system error converges in fixed time, preventing a ”computational explosion” while maintaining the transient performance of the system. Additionally, an event-triggered mechanism (ETM) is incorporated to mitigate the communication resource burden on the system. Finally, simulation experiments validate the efficacy of the proposed control strategy.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107638"},"PeriodicalIF":3.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 Rao-type tests for step-stress accelerated lifetests with interval-censored data and Weibull lifetime distributions

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-18 DOI: 10.1016/j.jfranklin.2025.107650

Narayanaswamy Balakrishnan , María Jaenada , Leandro Pardo

{"title":"Robust Rao-type tests for step-stress accelerated lifetests with interval-censored data and Weibull lifetime distributions","authors":"Narayanaswamy Balakrishnan , María Jaenada , Leandro Pardo","doi":"10.1016/j.jfranklin.2025.107650","DOIUrl":"10.1016/j.jfranklin.2025.107650","url":null,"abstract":"<div><div>Many engineering products are highly reliable in the present highly competitive market, often exhibiting long mean lifetimes to failure. This makes experimental testing both time-intensive and challenging. Accelerated life-tests are commonly used to induce early failures by subjecting products to higher-than-normal stress conditions, enabling enough failures to be observed for accurate statistical analysis. Additionally, censored data is a common challenge in reliability studies. Specifically, interval-censored data arises when continuous monitoring of devices is impractical or infeasible due to technical constraints or budget limitations. Statistical inference in such situations is often based on the likelihood function of the model. However, likelihood-based methods can be highly sensitive to outliers, which may result in biased or unreliable estimates. To address this issue, minimum density power divergence techniques can be used as a robust alternative. These methods extend traditional likelihood-based approach and have demonstrated appealing performance in reliability inference. In this paper, we develop robust restricted estimators based on the density power divergence for step-stress accelerated life-tests under Weibull distributions with interval-censored data and use these restricted estimators to generalize the Rao Score test for testing composite null hypotheses, including testing the significance of stress factors contributing degradation of the devices. We present the theoretical asymptotic properties of the estimators and also associated test statistics, along with numerical analyses that support the robustness of the proposed estimators and tests of hypotheses.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107650"},"PeriodicalIF":3.7,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Integration of adaptive projection BFGS and inertial extrapolation step for nonconvex optimization problems and its application in machine learning

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-17 DOI: 10.1016/j.jfranklin.2025.107652

Gonglin Yuan , Yuehan Yang , Yong Li , Xiong Zhao , Zehong Meng

{"title":"Integration of adaptive projection BFGS and inertial extrapolation step for nonconvex optimization problems and its application in machine learning","authors":"Gonglin Yuan , Yuehan Yang , Yong Li , Xiong Zhao , Zehong Meng","doi":"10.1016/j.jfranklin.2025.107652","DOIUrl":"10.1016/j.jfranklin.2025.107652","url":null,"abstract":"<div><div>With the rapid development of machine learning and large data technologies, large-scale optimization problems become more and more common, and traditional optimization algorithms face the challenges of computational complexity and memory consumption. In this paper, we combine the adaptive projection BFGS method with the inertial extrapolation technique, and propose a BFGS algorithm combining inertial extrapolation and adaptive projection, which enhances the search capability of the algorithm, ensures that there is a suitable descent direction in each iteration, and reduces the oscillation in the iteration. Under certain mild conditions and weak Wolfe–Powell (WWP) conditions, the algorithm demonstrates both global convergence and superlinear convergence rates for nonconvex unconstrained optimization problems. In addition, to solve large-scale optimization problems, we propose an inertial extrapolation adaptive projection BFGS algorithm based on variance reduction, which performs well in dealing with large-scale datasets and offers new insights to address the limitations of traditional algorithms. Finally, we evaluate their performance and efficiency using classical numerical experiments and applications in machine learning models.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107652"},"PeriodicalIF":3.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

H∞ state estimation for delayed neural networks via variable-augmented-based free-weighting matrices method

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-17 DOI: 10.1016/j.jfranklin.2025.107647

Xu-Kang Chang, Yong He

{"title":"H∞ state estimation for delayed neural networks via variable-augmented-based free-weighting matrices method","authors":"Xu-Kang Chang, Yong He","doi":"10.1016/j.jfranklin.2025.107647","DOIUrl":"10.1016/j.jfranklin.2025.107647","url":null,"abstract":"<div><div>The issue of <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> state estimation for neural networks with time-varying delays is investigated in this study. Firstly, an augmented Lyapunov-Krasovskii functional (LKF) with two delay-product-type terms is constructed to enhance the consideration of system state, delay, and delay derivative information. Furthermore, for taking into account more effective information, the LKF is augmented with both single and double integral variables. Accordingly, the LKF derivative becomes a higher-order term that exhibits nonlinear characteristics of the time delay. To solve the nonlinear problem, a variable-augmented-based free-weighting-matrices (VAFWMs) approach is employed to transform the nonlinear term into a linear form and provides more freedom in obtaining less-conservative results. Consequently, two improved <span><math><msub><mrow><mi>H</mi></mrow><mrow><mi>∞</mi></mrow></msub></math></span> state estimation criteria are derived. Lastly, a numerical example is provided to demonstrate the merits and effectiveness of the presented methods. Meanwhile, to prove the practical viability of the presented methods, this study extends the methods to a real-world quadruple-tank process system.</div></div>","PeriodicalId":17283,"journal":{"name":"Journal of The Franklin Institute-engineering and Applied Mathematics","volume":"362 7","pages":"Article 107647"},"PeriodicalIF":3.7,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143683633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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

Quaternion kernel partial least squares regression algorithms

IF 3.7 3区计算机科学

Journal of The Franklin Institute-engineering and Applied Mathematics Pub Date : 2025-03-15 DOI: 10.1016/j.jfranklin.2025.107651

José Domingo Jiménez-López, Rosa María Fernández-Alcalá, Jesús Navarro-Moreno, Juan Carlos Ruiz-Molina

引用次数: 0