Chaos Solitons & Fractals最新文献

{"title":"Hardware implementation and information security application of a novel chaotic system with a cubic memristor and complex parameters","authors":"Cuimei Jiang ,&nbsp;Yunxiao Ye ,&nbsp;Fangfang Zhang ,&nbsp;Lei Kou ,&nbsp;Han Bao ,&nbsp;Jianlin Zhang ,&nbsp;Hongjun Liu","doi":"10.1016/j.chaos.2025.116379","DOIUrl":"10.1016/j.chaos.2025.116379","url":null,"abstract":"<div><div>The inherent properties of chaos offer significant potential for information security, especially in cryptographic applications like image encryption. Therefore, a novel complex chaotic system with a memristor and complex parameters is proposed, its dynamic behaviors are investigated, and its hardware implementation is provided. Parameter-dominated attractors are identified and a precise definition is established. The system exhibits an extensive chaotic region and a broad parameter range, enabling the production of infinitely long key streams. A novel image encryption scheme is proposed by integrating the Advanced Encryption Standard with the proposed chaotic system. This system features a new key generation algorithm and a dynamic Substitution-box algorithm. Rigorous experimentation and security analysis confirm that the proposed algorithm successfully mitigates adjacent pixel correlation while exhibiting strong resilience against various attacks. The proposed method will advance the development of complex chaotic cryptography and establish a foundation for its industrial applications in information security.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116379"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Resampled interval control for prescribed-time bipartite synchronization of signed networks","authors":"Min Xiao ,&nbsp;Zhongtian Gao ,&nbsp;Tianrui Chen ,&nbsp;Ju H. Park","doi":"10.1016/j.chaos.2025.116343","DOIUrl":"10.1016/j.chaos.2025.116343","url":null,"abstract":"<div><div>This paper explores prescribed-time bipartite synchronization (PTBS) of signed networks by employing resampled interval control (RIC). With the introduction of an interval adjustment parameter sequence, the control input can be adjusted dynamically, which makes the control strategy both effective and economical. Under this control strategy, bipartite synchronization can be achieved within the prescribed time. Subsequently, a Lyapunov function is constructed with an auxiliary function and Kirchhoff’s matrix tree theorem is introduced to derive the sufficient condition for achieving PTBS under RIC. Finally, a numerical example of Chua’s circuits (CCs) is exhibited to demonstrate the effectiveness of the theoretical analysis.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116343"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multiple soliton solutions and other scientific solutions for a new Painlevé integrable fifth-order equation","authors":"Abdul-Majid Wazwaz","doi":"10.1016/j.chaos.2025.116307","DOIUrl":"10.1016/j.chaos.2025.116307","url":null,"abstract":"<div><div>In this work, we introduce a new Painlevé integrable fifth–order equation. We employ the Painlevé integrability test to examine the compatibility conditions for this newly established system. We use the dispersion relation, the phase shift, and the Hirota’s method to derive multiple soliton solutions for this equation. We also derive several other solutions of distinct physical structures. The obtained results enrich the KdV system and explore valuable analysis for the solitary wave phenomena.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116307"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prescribed-time stabilization of stochastic complex dynamical networks with aperiodically intermittent pinning control","authors":"Ying Guo ,&nbsp;Xiaotong Liu ,&nbsp;Xue Long ,&nbsp;Junning Zhang","doi":"10.1016/j.chaos.2025.116341","DOIUrl":"10.1016/j.chaos.2025.116341","url":null,"abstract":"<div><div>In this paper, a new type of aperiodically intermittent pinning control (AIPC) is proposed to investigate the prescribed-time stabilization (PTS) of stochastic complex dynamical networks (SCDNs). It is worth noting that the paper provides a theorem for realizing PTS for SCDNs under AIPC and affords a corollary of the relationship between the state of the nodes of the SCDNs and the control gain of AIPC. Besides, using the Lyapunov method and graph theory, SCDNs under AIPC can reach PTS at the given settling time, when only some of the nodes of SCDNs need to be controlled during the aperiodically intermittent control time. Compared to the existing literature, the AIPC in this paper no longer emphasizes that SCDNs must be strongly connected, but simply need to be connected. Furthermore, the theoretical results are employed to Chua’s chaotic circuits and a numerical simulation is offered to support the validity of the theoretical results.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116341"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explosive synchronization driven by repulsive higher-order interactions in coupled neurons","authors":"Agustin Farrera-Megchun ,&nbsp;Pablo Padilla-Longoria ,&nbsp;Gerardo J. Escalera Santos ,&nbsp;Jesús Espinal-Enríquez ,&nbsp;Roberto Bernal-Jaquez","doi":"10.1016/j.chaos.2025.116368","DOIUrl":"10.1016/j.chaos.2025.116368","url":null,"abstract":"<div><div>Neuron synchronization plays a crucial role in brain dynamics. Although considerable progress has been made in the understanding of synchronization, the study in neuronal models within higher-order networks remains insufficiently understood. This study explores the impact of repulsive higher-order interactions in a weighted network of coupled Huber-Braun (HB) neurons, focusing on how these interactions influence the dynamics of synchronization and firing patterns. Our numerical simulations reveal that repulsive higher-order interactions can induce irreversible explosive transitions in synchronization, characterized by sudden and abrupt shifts in the network’s collective state. Additionally, with bifurcation diagrams and phase portraits, we also identify irreversible transitions in firing patterns, highlighting the presence of multistability within the system. Coexistence between dynamics is observed, such as period-1 and period-2 bursting, period-3 bursting and chaotic dynamics. These findings contribute to a deeper understanding of how higher-order interactions affect neuronal dynamics, offering insights into the mechanisms behind explosive synchronization and its implications for neural network behavior.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116368"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dynamic resilience in complex networks","authors":"Xingyu Pan,&nbsp;Zerong Guo","doi":"10.1016/j.chaos.2025.116369","DOIUrl":"10.1016/j.chaos.2025.116369","url":null,"abstract":"<div><div>Many real-world systems comprise fundamental elements that exhibit mutual exclusion and alternating activation. Here, we develop a framework for the evolution of network structures that captures the behaviors of such systems. We define the dynamic resilience of temporal networks using variational rates to measure how the evolutionary trajectories of network structures diverge under perturbations. We show that perturbations to specific edges and states of mutually exclusive elements can cause evolutionary trajectories of network structures to deviate significantly from the original path. Furthermore, we demonstrate that traditional resilience factors do not affect dynamic resilience, which is instead governed by mutual exclusion within our framework. Our results advance the study of network resilience, particularly for networks with evolving structures, offering a novel perspective for identifying crucial perturbations within the context of the states of mutually exclusive elements.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116369"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785983","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Discrete homogeneous Moran sets on Z","authors":"Yi Lu,&nbsp;Jingjing Chen,&nbsp;Lifeng Xi","doi":"10.1016/j.chaos.2025.116382","DOIUrl":"10.1016/j.chaos.2025.116382","url":null,"abstract":"<div><div>Moran fractal (Wen, 2001) is significant in the field of Fractal Geometry. The discrete Moran sets on <span><math><mi>Z</mi></math></span> with the same expansion factor was discussed in Yao et al. (2024). This paper explores the fractal dimensions of discrete homogeneous Moran sets on <span><math><mi>Z</mi></math></span>, where each step involves a distinct expansion factor.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116382"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial neural networks framework for investigating Hall and ion slip dynamics in Prandtl nanofluids using non-Fourier heat and mass transfer models","authors":"Muhammad Idrees Afridi ,&nbsp;Shazia Habib ,&nbsp;Bandar Almohsen ,&nbsp;Zeeshan Khan ,&nbsp;Raheela Razzaq","doi":"10.1016/j.chaos.2025.116408","DOIUrl":"10.1016/j.chaos.2025.116408","url":null,"abstract":"<div><div>Artificial neural networks (ANNs) are widely applied in fluid mechanics and engineering to model complex relationships between input and output data. They facilitate pattern recognition, process optimization, and material property prediction. This study focuses on resolving the Hall ion effect in Prandtl nanofluid using a non-Fourier double diffusion theory-based model (HIE-PNF-NFDDT). The Levenberg-Marquardt backpropagated neural network (LMBNN) method is employed to analyze temperature, velocity, and concentration distributions. The dataset for training the ANN is obtained using the bvp4c solver. The study investigates the impact of the Hall effect and ion slip phenomena on the Cattaneo-Christov double heat flow model, leveraging the LMBNN algorithm to obtain solutions. Results indicate a direct correlation between velocity and the Hall parameter. Temperature increases with the Brownian motion parameter but decreases as the Hall parameter rises. Similarly, concentration increases with the Hall parameter but exhibits an inverse relationship with the relaxation time parameter. The performance of the proposed ANN model is evaluated using key metrics range of Mean Squared Error is detected as <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>9</mn></mrow></msup><mo>−</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>10</mn></mrow></msup></math></span>, while the Error Histograms ranges between <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>05</mn></mrow></msup><mo>−</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>07</mn></mrow></msup></math></span>.The gradient lies near <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>08</mn></mrow></msup></math></span>, while the <span><math><mi>Mu</mi></math></span> ranges between the interval <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>08</mn></mrow></msup><mo>−</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>09</mn></mrow></msup></math></span>. The AE lies in <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>03</mn></mrow></msup><mo>−</mo><msup><mn>10</mn><mrow><mo>−</mo><mn>08</mn></mrow></msup></math></span>, which shows the accuracy and reliability of the suggested method. The proposed approach demonstrates rapid convergence, efficient modeling, and reduced computational costs, making it a powerful tool for solving complex nonlinear problems in engineering and fluid mechanics.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116408"},"PeriodicalIF":5.3,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143785984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The interplay of passing, driver attention, and cyber attack-induced information delays on traffic stability","authors":"Darshana Yadav ,&nbsp;Vikash Siwach ,&nbsp;Poonam Redhu","doi":"10.1016/j.chaos.2025.116366","DOIUrl":"10.1016/j.chaos.2025.116366","url":null,"abstract":"<div><div>With the growing integration of Advanced Driver Assistance Systems (ADAS) in modern vehicles, cybersecurity threats present substantial risks to traffic stability and safety. This study introduces an advanced car-following model that accounts for the effects of passing, driver attention, and information delays caused by cyberattacks, and investigates their impact on traffic dynamics within ADAS systems. To understand how perturbations evolve over time, stability analysis is performed. Linear stability analysis identifies the conditions for neutral stability, while nonlinear analysis, using the reductive perturbation method, reveals stable, metastable, and unstable traffic states. The results show that a lower passing rate slightly reduces congestion while maintaining the same flow pattern, whereas a higher passing rate leads to a transition from congested to chaotic flow. Our findings also suggest that cyber intrusions exacerbate instability, while information from leading vehicles helps to enhance stability. Random, variable cyberattack intensity on vehicles is found to be more detrimental to stability than a constant, uniform impact, making traffic flow more unpredictable. Furthermore, spectral entropy is used to quantify traffic disruptions caused by cyberattacks, emphasizing the importance of driver attention and information exchange in mitigating instability. This study provides valuable insights into the interaction between cybersecurity and traffic stability, contributing to the development of more resilient ADAS-based transportation systems.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116366"},"PeriodicalIF":5.3,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143783914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Universal behavior of the two-times correlation functions of random processes with renewal","authors":"Marco Bianucci ,&nbsp;Mauro Bologna ,&nbsp;Daniele Lagomarsino-Oneto ,&nbsp;Riccardo Mannella","doi":"10.1016/j.chaos.2025.116351","DOIUrl":"10.1016/j.chaos.2025.116351","url":null,"abstract":"<div><div>Stochastic processes with renewal properties, or semi-Markovian processes, have emerged as powerful tools for modeling phenomena where the assumption of complete independence between temporally spaced events is unrealistic. These processes find applications across diverse disciplines, including biology, neuroscience, health sciences, social sciences, ecology, climatology, geophysics, oceanography, chemistry, physics, and finance. Investigating their statistical properties is crucial for understanding complex systems. Here we obtain a simple exact expression for the two-times correlation function, a key descriptor of renewal processes, as it determines the power spectrum and impacts the diffusion properties of systems influenced by such processes. Although results for the two-times correlation function have been derived, the exact expression has been evaluated only for some specific cases, as for systems with <span><math><mi>N</mi></math></span> states notably the simplest is the dichotomous scenario. By averaging over trajectory realizations, we obtain a universal result for the two-times correlation function, independent of the jump statistics, provided the variance is finite. Under the standard assumption for reaching asymptotic stationarity, where waiting times decay as <span><math><msup><mrow><mi>t</mi></mrow><mrow><mo>−</mo><mi>μ</mi></mrow></msup></math></span> with <span><math><mrow><mi>μ</mi><mo>&gt;</mo><mn>2</mn></mrow></math></span>, we show that stationarity depends solely on the first time <span><math><msub><mrow><mi>t</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>, i.e., the time distance from the preparation time, while the time difference <span><math><mrow><msub><mrow><mi>t</mi></mrow><mrow><mn>2</mn></mrow></msub><mo>−</mo><msub><mrow><mi>t</mi></mrow><mrow><mn>1</mn></mrow></msub></mrow></math></span> is inconsequential. For systems where stationarity is unattainable (<span><math><mrow><mn>1</mn><mo>&lt;</mo><mi>μ</mi><mo>&lt;</mo><mn>2</mn></mrow></math></span>), we provide a universal asymptotic form of the correlation function for large <span><math><msub><mrow><mi>t</mi></mrow><mrow><mn>1</mn></mrow></msub></math></span>, extending previous results limited to specific time difference regimes. We examine two interpretations of renewal processes: shot noise and step noise—, relevant to physical systems such as general Continuous Time Random Walks and Lévy walks with random velocities. While this study focuses on two-times correlations, the simple methodology is generalizable to <span><math><mi>n</mi></math></span>-times correlations, offering a pathway for future research into the statistical mechanics of renewal processes.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116351"},"PeriodicalIF":5.3,"publicationDate":"2025-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143776567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}