Chaos Solitons & Fractals最新文献

{"title":"Fast and slow dynamical behaviors of delayed-coupled thermosensitive neurons under electromagnetic induction","authors":"Yansu Ji,&nbsp;Xiaochen Mao","doi":"10.1016/j.chaos.2024.115721","DOIUrl":"10.1016/j.chaos.2024.115721","url":null,"abstract":"<div><div>This paper studies the dynamics of a thermosensitive neuronal network with delayed chemical synapses under electromagnetic induction. The stability and different bifurcations of the network are analyzed. Abundant and interesting bursting oscillations are explored, such as point–point bursting, cycle–cycle bursting, point-cycle bursting and cycle-point bursting oscillations. Time delay plays important roles in the system dynamics, including the amplitude of the spiking state and the delay interval of the subcritical Hopf bifurcation. The average Hamiltonian energy is considered to estimate the synchronized behaviors between neurons, such as intermittent synchronization. As the strength of the chemical synapses varies, asynchronous behaviors, intermittently synchronized and fully synchronized states are observed. The influences of the feedback strength gain of external stimuli induced by electromagnetic induction and temperature coefficient on the synchronized dynamics are discussed. Based on the exponential function circuit, time delay circuit and transfer function circuit, the circuit platform of the network is constructed. The responses of the circuit reach an agreement with the obtained results.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115721"},"PeriodicalIF":5.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650736","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":"A novel neural networks with memristor coupled memcapacitor-synapse neuron","authors":"Fan Shi ,&nbsp;Yinghong Cao ,&nbsp;Santo Banerjee ,&nbsp;Adil M. Ahmad ,&nbsp;Jun Mou","doi":"10.1016/j.chaos.2024.115723","DOIUrl":"10.1016/j.chaos.2024.115723","url":null,"abstract":"<div><div>With the increased understanding of information transfer and interactions between neurons, there is an urgent need for a memory element with bionic properties to probe the activity between neurons. Based on this, this paper constructs a novel Memristor Coupled Memcapacitor Synapse Hopfield Neural (MCMSHN) network by creating an element with a memristor coupled memcapacitor and applying it to a Hopfield neural network to simulate synaptic function. Firstly, the memory properties possessed by the Memristor Coupled Memcapacitor Synapse (MCMS) are demonstrated. Secondly, the complex dynamic behavior of MCMSHN is explored by means of numerical simulations to demonstrate its bionic properties. And the study focuses on the dynamical behavior of the synaptic weights and the coupling strengths, including multiple bifurcation behaviors, bionic discharges, and extreme multistability features of the MCMSHN. Finally, the attractors generated by the system are realized by Digital Signal Processing (DSP) techniques. The feasibility of MCMS for estimating synaptic activity is verified from multiple perspectives, providing insights into the complex working mechanisms of the brain.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115723"},"PeriodicalIF":5.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650735","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":"Generalized fined-grained multiscale information entropy with multi-feature extraction and its application in phase space reconstruction","authors":"Yupeng Shen,&nbsp;Yaan Li,&nbsp;Weijia Li,&nbsp;Quanmao Yao","doi":"10.1016/j.chaos.2024.115710","DOIUrl":"10.1016/j.chaos.2024.115710","url":null,"abstract":"<div><div>Phase space reconstruction plays an indispensable role in nonlinear engineering applications, and the quality of the reconstructed attractor depends on the optimal estimation of delay time and embedding dimension. This study mainly proposes a novel solution strategy for optimal delay time, which can lead to statistically equivalent reconstructions. First, a novel generalized fined-grained multiscale information entropy with multi-feature extraction (GFMIEME) is proposed, which exhibits excellent separability for various noises and chaotic signals. GFMIEME can preserve more original information and features of the target signals while ensuring processing efficiency. The design of multi-feature extraction helps to solve the problem that the mutation features are smoothed in multi-scale analysis, such as the violent fluctuations of signal amplitude and frequency are weakened. Then, based on GFMIEME, an improved mutual information method is developed to estimate delay time precisely. This method ensures the optimal estimation of the delay time for target signals through multiscale and multi-feature analysis. Final, phase space reconstruction is performed on the chaotic signals generated by the Lorenz and Liu systems to evaluate the effectiveness of the GFMIEME-based mutual information method to estimate the optimal delay time. Moreover, the robustness of the proposed method to noise under different signal-to-noise ratios (SNRs) is analyzed. The simulation results illustrate that the improved mutual information method can extract multiscale and multi-feature information from chaotic signals, and estimate the optimal delay time. The reconstructed attractors have a topological structure similar to the original system. Compared with the traditional delay time estimation methods, the proposed GFMIEME-based mutual information method exhibits better robustness to noise. When the SNR reaches -25 dB, the optimal delay times of the Lorenz and Liu attractors can still be estimated successfully.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115710"},"PeriodicalIF":5.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650840","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":"New disordered phases of the (s,1/2)-mixed spin Ising model for arbitrary spin s","authors":"Hasan Akın","doi":"10.1016/j.chaos.2024.115733","DOIUrl":"10.1016/j.chaos.2024.115733","url":null,"abstract":"<div><div>In this paper, we introduce an Ising model with mixed spin <span><math><mrow><mo>(</mo><mi>s</mi><mo>,</mo><mn>1</mn><mo>/</mo><mn>2</mn><mo>)</mo></mrow></math></span> (abbreviated as <span><math><mrow><mo>(</mo><mi>s</mi><mo>,</mo><mn>1</mn><mo>/</mo><mn>2</mn><mo>)</mo></mrow></math></span>-MSIM) for any spin set <span><math><mrow><mrow><mo>[</mo><mo>−</mo><mi>s</mi><mo>,</mo><mi>s</mi><mo>]</mo></mrow><mo>∩</mo><mi>Z</mi></mrow></math></span> on a semi-infinite second-order Cayley tree and construct translation-invariant splitting Gibbs measures (TISGMs) associated with the model. We prove that as the weight of the <span><math><mi>s</mi></math></span>-spin value increases, the repelling region of the fixed point <span><math><msubsup><mrow><mi>ℓ</mi></mrow><mrow><mn>0</mn></mrow><mrow><mrow><mo>(</mo><mi>s</mi><mo>)</mo></mrow></mrow></msubsup></math></span>, corresponding to the TISGM, expands, leading to a broadening of the phase transition region. We also study tree-indexed Markov chains associated with the <span><math><mrow><mo>(</mo><mi>s</mi><mo>,</mo><mn>1</mn><mo>/</mo><mn>2</mn><mo>)</mo></mrow></math></span>-MSIM. Additionally, we clarify the extremality of the associated disordered phases by utilizing the method of Martinelli, Sinclair, and Weitz (Martinelli et al., 2007). By examining the non-extremality of the disordered phases related to the <span><math><mrow><mo>(</mo><mi>s</mi><mo>,</mo><mn>1</mn><mo>/</mo><mn>2</mn><mo>)</mo></mrow></math></span>-MSIM on the Cayley tree using the Kesten–Stigum condition, we extend previous research findings to encompass any set of spins in <span><math><mrow><mrow><mo>[</mo><mo>−</mo><mi>s</mi><mo>,</mo><mi>s</mi><mo>]</mo></mrow><mo>∩</mo><mi>Z</mi></mrow></math></span>. Furthermore, we prove that as the weight of the <span><math><mi>s</mi></math></span>-spin value increases, the region where the disordered phase corresponding to the <span><math><mrow><mo>(</mo><mi>s</mi><mo>,</mo><mn>1</mn><mo>/</mo><mn>2</mn><mo>)</mo></mrow></math></span>-MSIM is extreme narrows, while the region where it is non-extreme widens.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115733"},"PeriodicalIF":5.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650737","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":"Impact of directionality on the emergence of Turing patterns on m-directed higher-order structures","authors":"Marie Dorchain ,&nbsp;Wilfried Segnou ,&nbsp;Riccardo Muolo ,&nbsp;Timoteo Carletti","doi":"10.1016/j.chaos.2024.115730","DOIUrl":"10.1016/j.chaos.2024.115730","url":null,"abstract":"<div><div>We hereby develop the theory of Turing instability for reaction–diffusion systems defined on <span><math><mi>m</mi></math></span>-directed hypergraphs, the latter being a generalization of hypergraphs where nodes forming hyperedges can be shared into two disjoint sets, the head nodes and the tail nodes. This framework encodes thus for a privileged direction for the reaction to occur: the joint action of tail nodes is a driver for the reaction involving head nodes. It thus results a natural generalization of directed networks. Based on a linear stability analysis, we have shown the existence of two Laplace matrices, allowing to analytically prove that Turing patterns, stationary or wave-like, emerge for a much broader set of parameters in the <span><math><mi>m</mi></math></span>-directed setting. In particular, directionality promotes Turing instability, otherwise absent in the symmetric case. Analytical results are compared to simulations performed by using the Brusselator model defined on a <span><math><mi>m</mi></math></span>-directed <span><math><mi>d</mi></math></span>-hyperring, as well as on a <span><math><mi>m</mi></math></span>-directed random hypergraph.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115730"},"PeriodicalIF":5.3,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650839","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":"A novel fractional-order grey Euler prediction model and its application in short-term traffic flow","authors":"Yuxin Song ,&nbsp;Huiming Duan ,&nbsp;Yunlong Cheng","doi":"10.1016/j.chaos.2024.115722","DOIUrl":"10.1016/j.chaos.2024.115722","url":null,"abstract":"<div><div>In intelligent transportation systems, short-term traffic flow prediction, as a core component, plays a crucial role in improving the operational efficiency and safety of the transportation system. To achieve accurate traffic flow prediction, a novel fractional-order grey Euler prediction model has been established. The new model utilizes the fractional-order accumulation technique and the characteristics of cycle truncation accumulated generating operation to develop a new fractional-order cycle truncation accumulating generation operator. By using this sequential operator for modeling, the new fractional-order operator can fully utilize new information promptly, reflect the dynamic and periodic characteristics of the traffic flow system, and flexibly capture short-term fluctuations in traffic flow data. By adjusting the parameters, the dynamic changes in the traffic flow system can be described more accurately. Meanwhile, the properties of this new fractional order operator are analyzed, the modeling conditions of this new sequential operator are verified, and the particle swarm algorithm is used to optimize the model parameters with the objective function of minimizing the average absolute percentage total error to improve the overall performance of the new model. Finally, the novel model is implemented to simulate and forecast traffic flow data on UK highways. Its performance is validated through a comprehensive analysis of traffic flows spanning three distinct periods, ensuring its robustness under varying traffic conditions. A comparative study with seven established grey prediction models reveals that our model surpasses them in both simulation and prediction outcomes, exhibiting remarkable stability and precision in both fitting and forecasting. Consequently, the integration of this new model into traffic flow analysis offers a potent tool to accurately depict traffic parameter trends, bolstering data adaptability and enhancing modeling capabilities significantly.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115722"},"PeriodicalIF":5.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650733","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":"Numerical approach and physical description for a two-capacitive neuron and its adaptive network dynamics","authors":"Yixuan Chen ,&nbsp;Qun Guo ,&nbsp;Xiaofeng Zhang ,&nbsp;Chunni Wang","doi":"10.1016/j.chaos.2024.115738","DOIUrl":"10.1016/j.chaos.2024.115738","url":null,"abstract":"<div><div>A simple neuron containing one capacitive variable can mimic the dynamical property of electrical activities in a biological neuron. Functional enhancement and activation of adaptive regulation must clarify the energy characteristic and nonlinear property of cell membrane of the neuron. In this work, two capacitors are connected via a nonlinear resistor for exploring the electrical activities in a double-layer nonlinear membrane, and the additive branch circuits are incorporated with piezoelectric ceramic and Josephson junction, which can perceive external acoustic wave and changes of magnetic field. The nonlinear equations for the neural circuit are converted into equivalent dimensionless neuron model in the form of nonlinear oscillator. The energy function for the neuron model is defined and proofed by using the Helmholtz theorem. Any mode transition is dependent on the shift of energy levels and coherence resonance is induced by noisy excitation. An adaptive control law under energy flow is proposed to regulate the firing patterns. Finally, the neuron is clustered to build a neural network with nearest neighbor coupling on a square array. Statistical synchronization factor is defined and calculated to predict the synchronization stability and wave propagation in the neural network. By activating the adaptive growth of coupling intensity and capacitance ratio for the outer and inner cell membrane, target like waves are developed in the neural network.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115738"},"PeriodicalIF":5.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650734","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":"Resonant responses and double-parameter multi-pulse chaotic dynamics of FG-GP reinforced rotating pre-twisted composite laminated blade under combined transverse aerodynamic force and parametric excitations","authors":"Y.Z. Lian ,&nbsp;W. Zhang ,&nbsp;Y.F. Zhang","doi":"10.1016/j.chaos.2024.115725","DOIUrl":"10.1016/j.chaos.2024.115725","url":null,"abstract":"<div><div>The new functionally grated graphene platelets (FG-GP) reinforced rotating pre-twisted composite laminated blade may exhibit strong nonlinear vibrations under combined the transverse aerodynamic force and axial excitation. These nonlinear vibrations are major contributors to the overall failure of the rotating pre-twisted composite laminated blade. In this paper, the resonant responses, threshold surface, global bifurcations and double-parameter multi-pulse chaotic dynamics of the rotating pre-twisted composite laminated blade are investigated on the basis of the nonlinear dynamic model of the new FG-GP reinforced rotating pre-twisted composite laminated blade for the first time. Considering the primary parametric and 1:1 internal resonances, the averaged equations for the new FG-GP reinforced rotating pre-twisted composite laminated blade are derived by using the multiple scale perturbation (MSP) method. The amplitude-frequency and force-amplitude response curves are obtained to analyze the resonant responses of the new FG-GP reinforced rotating pre-twisted composite laminated blade. The extended Melnikov method is used to explore the threshold surface, global bifurcations and double-parameter multi-pulse chaotic dynamics of the new FG-GP reinforced rotating pre-twisted composite laminated blade under combined the transverse aerodynamic force and axial excitation. Through the theoretical analysis and numerical simulation, it is discovered that the new FG-GP reinforced rotating pre-twisted composite laminated blade exhibits the hard spring characteristics. The energy transfers between two-order modes are proved by the occurrence of the bubble response shape. The complex double-parameter multi-pulse chaotic vibrations are investigated for the new FG-GP reinforced rotating pre-twisted composite laminated blade under the influence of different parameters. These results have the significant theoretical guidance for the optimized design of the new FG-GP reinforced rotating pre-twisted composite laminated blade.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115725"},"PeriodicalIF":5.3,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650729","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":"Analytical approximation of dynamic responses of random parameter nonlinear systems based on stochastic perturbation-Galerkin method","authors":"Bin Huang ,&nbsp;Cihang Ma ,&nbsp;Yejun Li ,&nbsp;Zhifeng Wu ,&nbsp;Heng Zhang","doi":"10.1016/j.chaos.2024.115724","DOIUrl":"10.1016/j.chaos.2024.115724","url":null,"abstract":"<div><div>The analytic approximation of dynamic responses is very significant for performing the optimization, parameter identification and reliability analysis of structural systems. However, the dynamic responses analysis of nonlinear random parameter systems is a challenging task due to the combined effects of randomness and strong nonlinearity. To address this problem, a new solution method based on the stochastic perturbation-Galerkin method is developed to obtain analytical solutions of the dynamic responses of single-degree-of-freedom nonlinear systems with random parameters. By combining the high-order perturbation and the Newmark-<em>β</em> method, the dynamic responses of systems are initially approximated using the power series expansions. Then a new approximation is defined for the Galerkin projection by utilizing the different orders of the power series expansion terms as trial functions. The employed Galerkin projection ensures the statistical minimization of the random error of the approximate series expansion. The numerical example shows that, for the first time, high-precision analytical expressions for the dynamic responses of a single-degree-of-freedom Duffing system with random parameters are obtained, even if the nonlinear coefficient reaches a value of 50. And it is found that the relationship between the dynamic responses and random variable is strongly nonlinear and constantly evolves over time, becoming increasingly complex along with the nonlinear coefficient. Numerical results further indicate that the new method owns superior computational accuracy compared with the perturbation method and the generalized polynomial chaos method of the same order, can better maintain convergence during long-time integration and has better efficiency than the direct Monte Carlo simulation method.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115724"},"PeriodicalIF":5.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650727","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":"Determination of a time dependent source in semilinear pseudoparabolic equations with Caputo fractional derivative","authors":"Kh. Khompysh","doi":"10.1016/j.chaos.2024.115716","DOIUrl":"10.1016/j.chaos.2024.115716","url":null,"abstract":"<div><div>This paper devoted to study unique solvability of inverse source problem for a semilinear time fractional pseudoparabolic equation perturbed by a damping term. Inverse problem consists of recovering a solely time dependent coefficient of right-hand side under a measurement in an integral form. The damped term acts in the equation as a nonlinear source or as an absorption, depending on its sign of coefficient, where it is positive or negative, respectively. In these both cases, we have established sufficient conditions on data, where the inverse problem has a global or local in time unique weak and strong solution.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"189 ","pages":"Article 115716"},"PeriodicalIF":5.3,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142650728","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}