Chaos Solitons & Fractals最新文献_第9页

Modulating propagation of Parkinsonian beta oscillations with transcranial direct current stimulation: A computational study 通过经颅直流电刺激调节帕金森病β振荡的传播：计算研究

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-12 DOI: 10.1016/j.chaos.2024.115635

{"title":"Modulating propagation of Parkinsonian beta oscillations with transcranial direct current stimulation: A computational study","authors":"","doi":"10.1016/j.chaos.2024.115635","DOIUrl":"10.1016/j.chaos.2024.115635","url":null,"abstract":"<div><div>Transcranial direct current stimulation (tDCS) is a non-invasive technique that primarily modulates cortical excitatory (E) neurons. Anodal tDCS targeting the motor cortex alleviates symptoms in Parkinson's disease patients, but the regulatory mechanisms remain obscure, especially for parkinsonian β band (13–30 Hz) oscillations. To explore these regulatory mechanisms, we propose a more refined model of the cortex-thalamic-basal ganglia (CTBG) neuronal network, with the primary issue of elucidating the impact of cortical neurons, as targets of tDCS, on parkinsonian β oscillations. Through blocking pathways, β oscillations in basal ganglia propagate to cortex mainly through thalamocortical connections, supplemented by direct connections from Lim homeobox 6 globus pallidus externa to cortical neurons. Simulations of two scenarios that lead to abnormal intracortical β band firing suggest that intracortical β band firing in healthy state is insufficient to drive β oscillations in CTBG circuit. This emphasizes the cortex as a critical node for the propagation and enhancement of β oscillations in CTBG circuit. To reveal the intrinsic regulatory mechanism of tDCS, different tDCS strategies targeting cortical E neurons are further compared. Anodal tDCS disrupts the abnormal oscillatory activity in CTBG circuits by promoting the activity of cortical neurons and interrupting oscillation propagation. In addition, anodic tDCS can amplify rhythmic activity within the afferent cortex, thereby concealing pathological oscillations. These findings provide a theoretical basis for understanding the role of cortex in parkinsonian oscillations and provide a conceptual platform for theoretical testing of tDCS for clinical applications.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419299","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}

引用次数: 0

Nonlinear chaotic Lorenz-Lü-Chen fractional order dynamics: A novel machine learning expedition with deep autoregressive exogenous neural networks 非线性混沌 Lorenz-Lü-Chen 分数阶动力学：利用深度自回归外源神经网络的新型机器学习探险

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-12 DOI: 10.1016/j.chaos.2024.115620

{"title":"Nonlinear chaotic Lorenz-Lü-Chen fractional order dynamics: A novel machine learning expedition with deep autoregressive exogenous neural networks","authors":"","doi":"10.1016/j.chaos.2024.115620","DOIUrl":"10.1016/j.chaos.2024.115620","url":null,"abstract":"<div><div>This exhaustive study entails fractional processing of the unified chaotic Lorenz-Lü-Chen attractors using machine learning expedition with Levenberg-Marquardt optimized deep nonlinear autoregressive exogenous neural networks (NARX-NNs-LM). The fractional Lorenz-Lü-Chen attractors (FLLCA) system is unified by three Caputo-based fractional differential equations reflecting Lorenz, Lü, Chen attractors exacted by the single control parameter. The Fractional Adams-Bashforth-Moulton predictor-corrector method is efficaciously employed for the FLLCA models for different variation of fractional orders to generate synthetic datasets for temporal anticipation and processing. Acquired datasets of FLLCA systems were arbitrarily split into a training, validation and test sets for the execution of nonlinear autoregressive exogenous neural networks optimized sequentially using the Levenberg-Marquardt algorithm. This refined NARX-NNs-LM strategy is validated across the reference numerical solutions via scrutiny on mean square error (MSE) convergence graphs, error histograms, regression indices, error autocorrelations, error input autocorrelations and time series response on exhaustive experimentation study on FLLCA systems. The predictive strength of the NARX-NNs-LM strategy is analyzed by means of step-ahead and multistep ahead predictors. Diminutive error metrics on sundry FLLCA scenarios reflect the expert utilization of NARX-NNs-LM for the precise examination, anticipation and forecasting of nonlinear chaotic fractional attractors.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419256","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}

引用次数: 0

Integrating Virtual and Physical Interactions through higher-order networks to control epidemics 通过高阶网络整合虚拟和物理互动，控制流行病

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-12 DOI: 10.1016/j.chaos.2024.115592

{"title":"Integrating Virtual and Physical Interactions through higher-order networks to control epidemics","authors":"","doi":"10.1016/j.chaos.2024.115592","DOIUrl":"10.1016/j.chaos.2024.115592","url":null,"abstract":"<div><div>In the context of our increasingly digitalized society, virtual interactions have become integral to daily communication, complementing traditional face-to-face interactions. These digital pathways, however, are often overlooked in the context of epidemic control, particularly in Digital Contact Tracing, where adoption rates of tailored wearable applications for this purpose remain suboptimal. This study elucidates the key role of the virtual environment in managing infectious disease outbreaks. We develop an integrated framework that combines various detection strategies to assess the efficacy of virtual tools in bending epidemic waves, analogous to conventional Contact Tracing approaches. Our analysis extends to the dynamics of higher-order interactions — characteristic of virtual platforms — and their contribution to epidemic control. Furthermore, we investigate the interplay between physical and virtual interactions, that aligned interactions optimize epidemic control in daily routine scenarios. Our findings underscore the critical role of virtual interactions in epidemic management, suggesting that current societal structures inherently support innovative detection and control strategies.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419343","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}

引用次数: 0

Nonlinear dynamics and sliding mode control for global fixed-time synchronization of a novel 2 × 2 memristor-based cellular neural network 基于忆阻器的新型 2 × 2 蜂窝神经网络的全局固定时间同步非线性动力学和滑动模式控制

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-11 DOI: 10.1016/j.chaos.2024.115611

{"title":"Nonlinear dynamics and sliding mode control for global fixed-time synchronization of a novel 2 × 2 memristor-based cellular neural network","authors":"","doi":"10.1016/j.chaos.2024.115611","DOIUrl":"10.1016/j.chaos.2024.115611","url":null,"abstract":"<div><div>The paper introduces a novel 2-dimensional 2 × 2 space-invariant cellular neural network (CNN) architecture, employing a current-controlled memristor to replace the resistor in one cell’s output. The CNN system is defined by space-invariant cloning templates and modeled as a fifth-order nonlinear system. Within the CNN system, non-symmetric double-wing chaotic attractors are exhibited, owing to the presence of two non-symmetric unstable equilibrium points, alongside one unstable equilibrium point located at the origin. Additionally, the paper delves into its nonlinear dynamics, ultimately determining that by adjusting the parameters of the memristor, the system exhibits chaotic and periodic attractors. Moreover, a locally sustained chaotic state is demonstrated across different initial conditions. The theoretical results are substantiated through circuit implementation. Furthermore, global fixed-time synchronization for the proposed CNN system with unmodeled dynamics and external disturbance is proposed by sliding mode control. The synchronization of the master–slave CNN system is achieved within a fixed converge time, independent on the initial conditions, and possesses a degree of robustness, as the synchronization times for CNNs with and without unmodeled dynamics and disturbances are nearly indistinguishable. The synchronization time can be manipulated by adjusting parameters of the sliding mode surface and the controller. The new discoveries pave a way for its applications to secure communications.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419297","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}

引用次数: 0

Probing Topological Superconductivity of oxide nanojunctions using fractional Shapiro steps 利用分数夏皮罗阶跃探测氧化物纳米结的拓扑超导性

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-11 DOI: 10.1016/j.chaos.2024.115596

引用次数: 0

A secondary optimization strategy in stochastic resonance modelling for the detection of unknown bearing faults 用于检测未知轴承故障的随机共振建模二次优化策略

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-11 DOI: 10.1016/j.chaos.2024.115576

{"title":"A secondary optimization strategy in stochastic resonance modelling for the detection of unknown bearing faults","authors":"","doi":"10.1016/j.chaos.2024.115576","DOIUrl":"10.1016/j.chaos.2024.115576","url":null,"abstract":"<div><div>Early fault diagnosis is a hot topic in the field of fault diagnosis. The collected vibration signals containing weak fault information are difficult to extract fault features due to the presence of strong background noise. Stochastic resonance (SR) is a signal processing method that can utilize noise to improve signal-to-noise ratio. However, SR mostly requires prior knowledge, such as the difficult to obtain bearing fault frequencies. A weighted piecewise bistable stochastic pooling network weak feature detection method based on a secondary optimization strategy is proposed in the paper. In the first layer of optimization, system parameters of each network unit are determined in the process of adaptive fault feature search based on Gini index. In the second layer of optimization, independent and identically distributed Gaussian white noise is added to each unit of the stochastic pooling network to enhance and extract weak signal features, and the unknown bearing fault types can be identified. The proposed method is applied to three different experimental datasets of bearing faults, and the diagnostic results all prove that compared to the single-layer optimization strategy, the proposed method has stronger weak signal enhancement ability and is more helpful for detecting unknown faults.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419300","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}

引用次数: 0

Design and analysis of a novel differential chaos shift keying system with joint three-dimensional index modulation 新型差分混沌移调键控系统与三维指数联合调制的设计与分析

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-10 DOI: 10.1016/j.chaos.2024.115609

{"title":"Design and analysis of a novel differential chaos shift keying system with joint three-dimensional index modulation","authors":"","doi":"10.1016/j.chaos.2024.115609","DOIUrl":"10.1016/j.chaos.2024.115609","url":null,"abstract":"<div><div>This paper proposes a joint three-dimensional index modulation differential chaos shift keying system, referred to as JTDIM-DCSK. To meet the demands of high-speed communication, this system employs k-combination mapping at the transmitter to achieve three-dimensional index modulation of carriers, time slots, and Walsh codes. This significantly increases the number of implicitly transmitted bits and allows for the transmission of multiple physical modulation bits within a single selected time slot. Additionally, the receiver uses two noise reduction modules for the reference signal and Walsh code index detection signal, effectively reducing noise interference and improving bit error rate (BER) performance. The theoretical BER of the JTDIM-DCSK system is derived under additive white Gaussian noise (AWGN) and multipath Rayleigh fading channels, confirming its accuracy. Furthermore, the paper conducts a comparative analysis of the proposed system with other structurally similar systems in terms of data rate, spectral efficiency, complexity, and BER. The results highlight the overall superior performance of the JTDIM-DCSK system, providing strong support for achieving high-quality wireless communication.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419266","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}

引用次数: 0

Adaptive dynamic event-triggered asymptotic control for uncertain nonlinear systems 不确定非线性系统的自适应动态事件触发渐近控制

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-10 DOI: 10.1016/j.chaos.2024.115597

引用次数: 0

Memory of fracture in information geometry 信息几何中的断裂记忆

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-10 DOI: 10.1016/j.chaos.2024.115608

{"title":"Memory of fracture in information geometry","authors":"","doi":"10.1016/j.chaos.2024.115608","DOIUrl":"10.1016/j.chaos.2024.115608","url":null,"abstract":"<div><div>In this study, the memory effect of the fracture phenomenon in information geometry is discussed. The input–output relation in a complex system as an application of fractional calculus generates the power law for the time and response time distribution, which determines the memory effect. The exponent of the response time distribution is related to the one of the various power laws for fracture phenomena, including earthquakes. The one of them is the shape parameter of the Weibull distribution, which indicates uniformity in the material. The exponent of the response time distribution is also linked to the magnitude of the change rate in the information density and the non-extensivity of the information in the statistical manifold for the response time distribution. From the discussion of the properties of their exponents, the memory effect of a fracture depends on the response time distribution with the uniformity of the material and reflects the information density for parameters related to the fracture and the non-extensivity of the information in the statistical manifold for the response time distribution. Moreover, we propose a method to understand fracture phenomena using information geometry for the response time distribution.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":null,"pages":null},"PeriodicalIF":5.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142419191","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}

引用次数: 0

Ratchet current and scaling properties in a nontwist mapping 非扭曲映射中的棘轮电流和缩放特性

IF 5.3 1区数学

Chaos Solitons & Fractals Pub Date : 2024-10-10 DOI: 10.1016/j.chaos.2024.115614

引用次数: 0