Chaos最新文献_第6页

Input signal accumulation capability of the FitzHugh-Nagumo neuron.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0243083

A V Bukh, I A Shepelev, T E Vadivasova

{"title":"Input signal accumulation capability of the FitzHugh-Nagumo neuron.","authors":"A V Bukh, I A Shepelev, T E Vadivasova","doi":"10.1063/5.0243083","DOIUrl":"https://doi.org/10.1063/5.0243083","url":null,"abstract":"We present numerical results on the effects of two presynaptic FitzHugh-Nagumo neurons on a postsynaptic neuron under unidirectional electrical coupling. The presynaptic neurons affect the postsynaptic neuron not simultaneously but with a certain time shift. We consider cases where the amplitudes of the presynaptic spikes can be both higher and lower than the excitation threshold level. The latter case receives the main attention in our work. We carefully examine the conditions under which the postsynaptic neuron is excited by the two asynchronous external spikes. With arbitrarily chosen parameters, the FitzHugh-Nagumo neuron is almost incapable of accumulating the energy of external signals, unlike, for example, the leaky integrate-and-fire neuron. In this case, the postsynaptic neuron only excites with a very short time delay between external impulses. However, we have discovered, for the first time, a parameter region where neuron excitation is possible even with significant time delays between presynaptic impulses with subthreshold amplitudes. We explain this effect in detail and describe the mechanism behind its occurrence. We identify the boundaries of this region in the parameter plane of time delay and coupling coefficient by varying the control parameter values of the neurons. The FitzHugh-Nagumo neuron has not previously been used as a node in spiking neural networks for training via spike-timing-dependent plasticity due to the lack of an integrate-and-fire effect. However, the detection of a certain range of parameters makes the potential application of this neuron for STDP training possible.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hopf-like bifurcations and multistability in a class of 3D Filippov systems with generalized Liénard's form.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0231485

Fanrui Wang, Zhouchao Wei, Wei Zhang, Tomasz Kapitaniak

引用次数: 0

A novel analytical tool for complex propagation processes in networks: High-order dynamic equation. 网络复杂传播过程的新型分析工具：高阶动态方程

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0223566

Jiahui Song, Zaiwu Gong

{"title":"A novel analytical tool for complex propagation processes in networks: High-order dynamic equation.","authors":"Jiahui Song, Zaiwu Gong","doi":"10.1063/5.0223566","DOIUrl":"https://doi.org/10.1063/5.0223566","url":null,"abstract":"Controlling the spread of epidemics in complex networks has always been an important research problem in the field of network science and has been widely studied by many scholars so far. One of the key problems in the transmission process of epidemics in complex networks is the transmission mechanism. At present, the transmission mechanism in complex networks can be divided into simple transmission and complex transmission. Simple transmission has been widely studied and the theory is relatively mature, while complex transmission still has many questions to answer. In fact, in the complex transmission process, the higher-order structure of the network plays a very important role, which can affect the transmission speed, final scale, and transmission path of the epidemic by strengthening the mechanism. However, due to the lack of complex dynamic analysis tools, the measurement of influence on propagation is still at the low-dimensional node level. Therefore, in this paper, we propose a set of closed dynamic higher-order structure equations to gain insight into the complex propagation process in the network, which breaks the inherent thinking and enables us to reexamine the complex dynamic behavior more clearly from the higher-order level rather than just from the node level, opening up a new way to analyze the higher-order interaction on the dynamic network. We apply the proposed high-order dynamic equations to a complex susceptible-infection-recovery epidemiological model on two real and synthetic networks, and extensive numerical simulation results demonstrate the effectiveness of the proposed approach. Our research results help to deepen the understanding of the relationship between complex propagation mechanisms and higher-order structures and develop a complete set of complex dynamic analysis tools that can be extended to higher-order forms to help in-depth understanding of the propagation rules and mechanisms in complex propagation processes, providing an important theoretical basis for predicting, analyzing, and controlling complex propagation processes.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142821971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Enhanced long short-term memory architectures for chaotic systems modeling: An extensive study on the Lorenz system. 用于混沌系统建模的增强型长短期记忆架构：对洛伦兹系统的广泛研究。

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0238619

Roland Bolboacă, Piroska Haller

引用次数: 0

Cooperation resonance based on link strategy reinforcement learning and conformity.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0239335

Bo Gao, Pengfei Zuo, Xiangfeng Dai, Rongrong Fu, Zhiyan Bai, Zhongzhou Lan

引用次数: 0

Distributed optimization consensus for multi-agent systems on matrix-weighted networks.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0235296

Suoxia Miao, Ruxin Xiong, Qing An, Cuihong Bao, Yaping Sun, Housheng Su

引用次数: 0

Tuning domain wall dynamics in a notched ferromagnetic nanostrip with Rashba effect.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0231491

Sarabindu Dolui, Sharad Dwivedi

引用次数: 0

Unsupervised data-driven response regime exploration and identification for dynamical systems.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0173938

Maor Farid

{"title":"Unsupervised data-driven response regime exploration and identification for dynamical systems.","authors":"Maor Farid","doi":"10.1063/5.0173938","DOIUrl":"https://doi.org/10.1063/5.0173938","url":null,"abstract":"Data-Driven Response Regime Exploration and Identification (DR2EI) is a novel and fully data-driven method for identifying and classifying response regimes of a dynamical system without requiring human intervention. This approach is a valuable tool for exploring and discovering response regimes in complex dynamical systems, especially when the governing equations and the number of distinct response regimes are unknown, and the system is expensive to sample. Additionally, the method is useful for order reduction, as it can be used to identify the most dominant response regimes of a given dynamical system. DR2EI utilizes unsupervised learning algorithms to transform the system's response into an embedding space that facilitates regime classification. An active sequential sampling approach based on Gaussian Process Regression is used to efficiently sample the parameter space, quantify uncertainty, and provide optimal trade-offs between exploration and exploitation. The performance of the DR2EI method was evaluated by analyzing three established dynamical systems: the mathematical pendulum, the Lorenz system, and the Duffing oscillator, and its robustness to noise was validated across a range of noise magnitudes. The method was shown to effectively identify a variety of response regimes with both similar and distinct topological features and frequency content, demonstrating its versatility in capturing a wide range of behaviors. While it may not be possible to guarantee that all possible regimes will be identified, the method provides an automated and efficient means for exploring the parameter space of a dynamical system and identifying its underlying \"sufficiently dominant\" response regimes without prior knowledge of the system's equations or behavior.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142766359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Evolutionary dynamics in spatial public goods games with environmental feedbacks.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0242366

Rui Ding, Xianjia Wang, Jinhua Zhao, Cuiling Gu, Wenman Chen

{"title":"Evolutionary dynamics in spatial public goods games with environmental feedbacks.","authors":"Rui Ding, Xianjia Wang, Jinhua Zhao, Cuiling Gu, Wenman Chen","doi":"10.1063/5.0242366","DOIUrl":"https://doi.org/10.1063/5.0242366","url":null,"abstract":"Collective actions aimed at achieving goals such as resource sustainability and environmental protection often face conflicting interests between individuals and groups. These social dilemmas can be modeled using public goods games and collective risk dilemmas. However, in reality, multiple generations share a common pool of resources, leading to high costs for today's overexploitation that impacts future generations' welfare. This delayed effect creates a multigenerational conflict. To address this, we develop a coupled social-ecological coevolutionary model by establishing a relationship between individual payoffs and regional environmental quality. Our goal is to study how cooperative behaviors spread in a public goods game with environmental feedback and to identify the factors influencing this spread. We achieve this by examining the mechanisms behind certain phases and phase transitions, monitoring the spatial distribution of strategies, and assessing the environmental quality of all regions. Our findings reveal some counterintuitive results. For instance, despite cooperators' ability to enhance the environment, the overall level of cooperation in the system sometimes decreases. This is linked to cooperative clusters being invaded by defectors within the clusters' cracks. Additionally, the destructive power of defection and the cost of cooperation have more complex effects on the system.","PeriodicalId":9974,"journal":{"name":"Chaos","volume":"34 12","pages":""},"PeriodicalIF":2.7,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142799578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Skeletal structure in domain of periodicity of the forced Brusselator.

IF 2.7 2区数学

Chaos Pub Date : 2024-12-01 DOI: 10.1063/5.0238883

Dariel M Maranhão, Rene O Medrano-T

引用次数: 0