Chaos Solitons & Fractals最新文献

英文中文

An agent-based model for simulating cooperative behavior in crowd evacuation during toxic gas terrorist attacks

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-10 DOI: 10.1016/j.chaos.2025.116397

Peng Lu , Yufei Li

Toxic gas leaks pose severe threats to public safety and societal stability, leading to large-scale casualties and social panic. This paper focuses on crowd evacuation behavior during toxic gas leak incidents, proposing an evacuation model that combines Computational Fluid Dynamics (CFD) and Agent-Based Modeling (ABM). By introducing a helping mechanism among agents with prosocial personalities, the study examines the impact of the prosocial personality ratio (p) on evacuation time, fatalities, and severe injuries. Subsequently, the effects of the p under varying conditions, such as total population size and evacuation response time, are explored. Additionally, a Random Forest model is employed to accurately predict evacuation risks, and the NSGA-III multi-objective optimization algorithm is utilized to identify the optimal range of p across different scenarios. The results indicate that a reasonable proportion of prosocial personalities can significantly reduce fatality rates and enhance overall evacuation efficiency. However, an excessively high proportion of prosocial individuals may increase crowd casualties due to extended delays caused by helping behaviors. This study contributes to the body of knowledge on public safety, provides methodological references for developing evacuation strategies during toxic gas diffusion incidents, and offers guidance for future emergency management practices.

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引用次数: 0

Broadband and time-delay signature suppressed chaos generation in semiconductor laser subjected to microring resonator combined with optical injection

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116417

Xiaojing Wei , Lijun Qiao , Zhiyong Guo , Xiaona Wang , Jian Li , Mingjiang Zhang

We experimentally investigate the evolutions of the chaotic characteristics in semiconductor laser subjected to microring resonator combined with optical injection. When the experimental parameters are changed, we calculate the standard bandwidth, flatness, and time-delay signature value of the chaotic laser. By the multiple beam interference effect, linear filtering effect and nonlinear self-phase modulation effect of microring resonator, as well as the beating frequency effect of optical injection, a chaotic laser with the standard bandwidth of 33.9 GHz, the flatness of ±3.7 dB, and the time-delay signature value of 0.08 is generated. Furthermore, the maps of the bandwidth, flatness and time-delay signature value of chaotic laser in the parameter space of the injection strength and frequency detuning are obtained. The results show that the chaotic laser with the bandwidth greater than 25.0 GHz, the flatness lower than ±5.0 dB, and the time-delay signature value lower than 0.10 can be generated simultaneously in a wide range of operating parameters.

{"title":"Broadband and time-delay signature suppressed chaos generation in semiconductor laser subjected to microring resonator combined with optical injection","authors":"Xiaojing Wei , Lijun Qiao , Zhiyong Guo , Xiaona Wang , Jian Li , Mingjiang Zhang","doi":"10.1016/j.chaos.2025.116417","DOIUrl":"10.1016/j.chaos.2025.116417","url":null,"abstract":"<div><div>We experimentally investigate the evolutions of the chaotic characteristics in semiconductor laser subjected to microring resonator combined with optical injection. When the experimental parameters are changed, we calculate the standard bandwidth, flatness, and time-delay signature value of the chaotic laser. By the multiple beam interference effect, linear filtering effect and nonlinear self-phase modulation effect of microring resonator, as well as the beating frequency effect of optical injection, a chaotic laser with the standard bandwidth of 33.9 GHz, the flatness of ±3.7 dB, and the time-delay signature value of 0.08 is generated. Furthermore, the maps of the bandwidth, flatness and time-delay signature value of chaotic laser in the parameter space of the injection strength and frequency detuning are obtained. The results show that the chaotic laser with the bandwidth greater than 25.0 GHz, the flatness lower than ±5.0 dB, and the time-delay signature value lower than 0.10 can be generated simultaneously in a wide range of operating parameters.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116417"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800315","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

Chaotic dynamics in an overlapping generations model: Forecasting and regularization 世代重叠模型中的混沌动力学：预测和正则化

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116371

Tatyana A. Alexeeva , Nikolay V. Kuznetsov , Timur N. Mokaev , Ivan Zelinka

Irregular dynamics (especially chaotic) is often undesirable in economics because it presents challenges for predicting and controlling the behavior of economic agents. In this paper, we used an overlapping generations (OLG) model with a control function in the form of government spending as an example, to demonstrate an effective approach to forecasting and regulating chaotic dynamics based on a combination of classical control methods and artificial intelligence algorithms. We showed that in the absence of control variables, both regular and irregular (including chaotic) behavior could be observed in the model. In the case of irregular dynamics, a small control action introduced in the model allows modifying the behavior of economic agents and switching their dynamics from irregular to regular mode. We used control synthesis by the Pyragas method to solve the problem of regularizing the irregular behavior and stabilizing unstable periodic orbits (UPOs) embedded in the chaotic attractor of the model. To maximize the basin of attraction of stabilized UPOs, we used several types of evolutionary algorithms (EAs). We compared the results obtained by applying these EAs in numerical experiments and verified the outcomes by numerical simulation. The proposed approach allows us to improve the forecasting of dynamics in the OLG model and make agents’ expectations more predictable.

{"title":"Chaotic dynamics in an overlapping generations model: Forecasting and regularization","authors":"Tatyana A. Alexeeva , Nikolay V. Kuznetsov , Timur N. Mokaev , Ivan Zelinka","doi":"10.1016/j.chaos.2025.116371","DOIUrl":"10.1016/j.chaos.2025.116371","url":null,"abstract":"<div><div>Irregular dynamics (especially chaotic) is often undesirable in economics because it presents challenges for predicting and controlling the behavior of economic agents. In this paper, we used an overlapping generations (OLG) model with a control function in the form of government spending as an example, to demonstrate an effective approach to forecasting and regulating chaotic dynamics based on a combination of classical control methods and artificial intelligence algorithms. We showed that in the absence of control variables, both regular and irregular (including chaotic) behavior could be observed in the model. In the case of irregular dynamics, a small control action introduced in the model allows modifying the behavior of economic agents and switching their dynamics from irregular to regular mode. We used control synthesis by the Pyragas method to solve the problem of regularizing the irregular behavior and stabilizing unstable periodic orbits (UPOs) embedded in the chaotic attractor of the model. To maximize the basin of attraction of stabilized UPOs, we used several types of evolutionary algorithms (EAs). We compared the results obtained by applying these EAs in numerical experiments and verified the outcomes by numerical simulation. The proposed approach allows us to improve the forecasting of dynamics in the OLG model and make agents’ expectations more predictable.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116371"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800309","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

Jamming transition of connected vehicles platform integrating speed change memory information to counteract cyber-attacks on slope lane 整合变速记忆信息的车联网平台的干扰过渡，以应对斜坡车道上的网络攻击

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116413

Guanghan Peng , Keke Wang , Huili Tan , Darong Huang

Under the connected environment, connected vehicles need to resist cyber-attacks such as tampered information in an open network of the traffic system. Additionally, slope lane is frequently seen in real traffic, which means that the gravitational action of the vehicles themselves cannot be ignored. Accordingly, a novel car-following model is constructed by aggregating the tampered speed difference (a type of cyber-attacks) with compensation and gravitational action on slope lane under connected vehicles environment (called for TSDCG model for simply). Moreover, we obtain the conditions for the traffic system to remain stable and the range of compensation parameters through cybernetics. Furthermore, numerical simulation is implemented for various intensities of the tampered speed difference. The results show that the tampered speed difference deteriorates the traffic system on both uphill and downhill. And on the contrary, the compensation can alleviate traffic congestion and effectively improve the stability of the traffic system when the connected vehicles are attacked by the tampered speed difference whether uphill or downhill. Also, the simulation results show that the compensation for the tampered speed difference can effectively reduce fuel consumption and pollutants emissions including CO, HC and NO_x.

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引用次数: 0

Reputation in public goods cooperation under double Q-learning protocol

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116398

Kai Xie , Attila Szolnoki

Understanding and resolving cooperation dilemmas are key challenges in evolutionary game theory, which have revealed several mechanisms to address them. This paper investigates the comprehensive influence of multiple reputation-related components on public cooperation. In particular, cooperative investments in public goods game are not fixed but simultaneously depend on the reputation of group organizers and the population’s cooperation willingness, hence indirectly impacting on the players’ income. Additionally, individual payoff can also be directly affected by their reputation via a weighted approach which effectively evaluates the actual income of players. Unlike conventional models, the reputation change of players is non-monotonic, but may transform abruptly due to specific actions. Importantly, a theoretically supported double

Q

-learning algorithm is introduced to avoid overestimation bias inherent from the classical

Q

-learning algorithm. Our simulations reveal a significantly improved cooperation level, that is explained by a detailed

Q

-value analysis. We also observe the lack of massive cooperative clusters in the absence of network reciprocity. At the same time, as an intriguing phenomenon, some actors maintain moderate reputation and are continuously flipping between cooperation and defection. The robustness of our results are validated by mean-field approximation.

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引用次数: 0

Induction of chimera states in Hindmarsh-Rose neurons through astrocytic modulation: Implications for learning mechanisms

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116414

Fatemeh Azad , Saeed Bagheri Shouraki , Soheila Nazari , Mansun Chan

Chimera states, a form of partial synchronization in neural networks, are characterized by the coexistence of synchronized and asynchronous regions. These states are crucial for various cognitive functions, such as learning and information processing. Conversely, abnormal synchronization—often referred to as hyper-synchronization—can lead to pathological conditions such as epilepsy and Parkinson's disease. Understanding the mechanisms underlying synchronization can provide valuable insights for developing effective therapeutic strategies for these disorders. Astrocyte, a primary type of glial cell, plays a pivotal role in modulating neural synchrony. They influence the synchronization threshold of neurons by providing feedback through the release of gliotransmitters, promoting group firing of neurons within the astrocyte's domain. This research aims to explore how astrocytes can facilitate the conversion of hyper-synchronized states into healthy chimera states within neural networks. This process is vital for maintaining normal brain function and may be critical to advancing treatments for neurological conditions. We analyzed how astrocytes can induce chimera states in nonlocally two-dimensional Hindmarsh-Rose neurons, which serve as realistic models of neuronal ensembles. Our findings demonstrate that astrocytes can effectively transition unhealthy hyper-synchronization states into healthy chimera states. Furthermore, by analyzing time spans, spatiotemporal patterns, inter-spike interval distributions (ISI), and phase plane diagrams of 2D H-R neurons, we validated our hypothesis about the crucial role of astrocytes in the development of chimera states. The outcomes may pave the way for innovative therapeutic approaches to restore normal neural activity patterns, ultimately improving patient outcomes in conditions such as epilepsy and Parkinson's disease.

{"title":"Induction of chimera states in Hindmarsh-Rose neurons through astrocytic modulation: Implications for learning mechanisms","authors":"Fatemeh Azad , Saeed Bagheri Shouraki , Soheila Nazari , Mansun Chan","doi":"10.1016/j.chaos.2025.116414","DOIUrl":"10.1016/j.chaos.2025.116414","url":null,"abstract":"<div><div>Chimera states, a form of partial synchronization in neural networks, are characterized by the coexistence of synchronized and asynchronous regions. These states are crucial for various cognitive functions, such as learning and information processing. Conversely, abnormal synchronization—often referred to as hyper-synchronization—can lead to pathological conditions such as epilepsy and Parkinson's disease. Understanding the mechanisms underlying synchronization can provide valuable insights for developing effective therapeutic strategies for these disorders. Astrocyte, a primary type of glial cell, plays a pivotal role in modulating neural synchrony. They influence the synchronization threshold of neurons by providing feedback through the release of gliotransmitters, promoting group firing of neurons within the astrocyte's domain. This research aims to explore how astrocytes can facilitate the conversion of hyper-synchronized states into healthy chimera states within neural networks. This process is vital for maintaining normal brain function and may be critical to advancing treatments for neurological conditions. We analyzed how astrocytes can induce chimera states in nonlocally two-dimensional Hindmarsh-Rose neurons, which serve as realistic models of neuronal ensembles. Our findings demonstrate that astrocytes can effectively transition unhealthy hyper-synchronization states into healthy chimera states. Furthermore, by analyzing time spans, spatiotemporal patterns, inter-spike interval distributions (ISI), and phase plane diagrams of 2D H-R neurons, we validated our hypothesis about the crucial role of astrocytes in the development of chimera states. The outcomes may pave the way for innovative therapeutic approaches to restore normal neural activity patterns, ultimately improving patient outcomes in conditions such as epilepsy and Parkinson's disease.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116414"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800313","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

Stochastic process rule-based Markov chain method for degree correlation of evolving networks

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116391

Yue Xiao, Xiaojun Zhang

There is yet to be a unified theoretical framework for defining and solving degree correlation in evolving networks, which limits applied research in evolving networks. To address this problem, we proposed a stochastic process-based Markov chain method. The transition rules of network nodes and edges designed in this method ensure that the network topology and statistical characteristics at any time are the same as those in natural evolution. Then, the Markov chain model constructed based on this rule gives the theoretical results of the steady-state joint degree distribution of directed pure growth networks and corresponding undirected networks. Finally, the accuracy of the solution was verified by Monte Carlo simulation, and the probability functions of the joint degree distribution under different parameters were given. This work not only provides a theoretical research framework for the steady-state degree correlation of evolving networks for the first time but is also applicable to the study of many complex network evolution mechanisms and high-order statistical characteristics. In addition, this method can also study the transient degree correlation of networks at any time, providing a new perspective for network dynamics control.

{"title":"Stochastic process rule-based Markov chain method for degree correlation of evolving networks","authors":"Yue Xiao, Xiaojun Zhang","doi":"10.1016/j.chaos.2025.116391","DOIUrl":"10.1016/j.chaos.2025.116391","url":null,"abstract":"<div><div>There is yet to be a unified theoretical framework for defining and solving degree correlation in evolving networks, which limits applied research in evolving networks. To address this problem, we proposed a stochastic process-based Markov chain method. The transition rules of network nodes and edges designed in this method ensure that the network topology and statistical characteristics at any time are the same as those in natural evolution. Then, the Markov chain model constructed based on this rule gives the theoretical results of the steady-state joint degree distribution of directed pure growth networks and corresponding undirected networks. Finally, the accuracy of the solution was verified by Monte Carlo simulation, and the probability functions of the joint degree distribution under different parameters were given. This work not only provides a theoretical research framework for the steady-state degree correlation of evolving networks for the first time but is also applicable to the study of many complex network evolution mechanisms and high-order statistical characteristics. In addition, this method can also study the transient degree correlation of networks at any time, providing a new perspective for network dynamics control.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116391"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800311","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

Dark-bright-dark rogue wave triplets within a partially nonlocal three-component nonlinear Schrödinger framework

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-09 DOI: 10.1016/j.chaos.2025.116384

Liang-Yuan Chen, Hong-Yu Wu

The partially nonlocal multi-component nonlinear Schrödinger system holds significant application potential for modeling partially nonlocal nonlinear responses in multi-division multiplexing optical information systems. However, research exploring three-component systems with distinct rogue wave configurations remains notably scarce. In this study, we address this gap by investigating a variable-coefficient (2+1)-dimensional partially nonlocal three-component nonlinear Schrödinger system, which is systematically reduced to a constant-coefficient three-component equation for analytical solution construction. By employing the Darboux transformation, we successfully derive partially nonlocal dark-bright-dark rogue wave triplet solutions. Furthermore, we comprehensively analyze various excitation regimes of these rogue wave triplets in the exponential diffraction system, including full, trailing, peak-maintaining, and inhibited excitations. This analysis is conducted through a comparative examination of the maximal accumulated time relative to the excited location parameters of the rogue wave triplets. The insights gained from this study significantly enhance our fundamental understanding of ultrashort wave phenomena observed across diverse physics and engineering domains.

{"title":"Dark-bright-dark rogue wave triplets within a partially nonlocal three-component nonlinear Schrödinger framework","authors":"Liang-Yuan Chen, Hong-Yu Wu","doi":"10.1016/j.chaos.2025.116384","DOIUrl":"10.1016/j.chaos.2025.116384","url":null,"abstract":"<div><div>The partially nonlocal multi-component nonlinear Schrödinger system holds significant application potential for modeling partially nonlocal nonlinear responses in multi-division multiplexing optical information systems. However, research exploring three-component systems with distinct rogue wave configurations remains notably scarce. In this study, we address this gap by investigating a variable-coefficient (2+1)-dimensional partially nonlocal three-component nonlinear Schrödinger system, which is systematically reduced to a constant-coefficient three-component equation for analytical solution construction. By employing the Darboux transformation, we successfully derive partially nonlocal dark-bright-dark rogue wave triplet solutions. Furthermore, we comprehensively analyze various excitation regimes of these rogue wave triplets in the exponential diffraction system, including full, trailing, peak-maintaining, and inhibited excitations. This analysis is conducted through a comparative examination of the maximal accumulated time relative to the excited location parameters of the rogue wave triplets. The insights gained from this study significantly enhance our fundamental understanding of ultrashort wave phenomena observed across diverse physics and engineering domains.</div></div>","PeriodicalId":9764,"journal":{"name":"Chaos Solitons & Fractals","volume":"196 ","pages":"Article 116384"},"PeriodicalIF":5.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800314","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

Charging free fermion quantum batteries

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-08 DOI: 10.1016/j.chaos.2025.116383

Riccardo Grazi, Fabio Cavaliere, Maura Sassetti, Dario Ferraro, Niccolò Traverso Ziani

The performances of many-body quantum batteries strongly depend on the Hamiltonian of the battery, the initial state, and the charging protocol. In this article we derive an analytical expression for the energy stored via a double sudden quantum quench in a large class of quantum systems whose Hamiltonians can be reduced to 2x2 free fermion problems, whose initial state is thermal. Our results apply to conventional two-band electronic systems across all dimensions and quantum spin chains that can be solved through the Jordan–Wigner transformation. In particular, we apply our analytical relation to the quantum Ising chain, to the quantum XY chain, to the cluster Ising and to the long range SSH models. We obtain several results: (i) The strong dependence of the stored energy on the quantum phase diagram of the charging Hamiltonian persists even when the charging starts from a thermal state. Interestingly, in the thermodynamic limit, such a strong dependence manifests itself as non-analyticities of the stored energy corresponding to the quantum phase transition points of the charging Hamiltonian. (ii) The dependence of the stored energy on the parameters of the Hamiltonian can, in the Ising chain case, be drastically reduced by increasing temperature; (iii) Charging the Ising or the XY chain prepared in the ground state of their classical points leads to an amount of stored energy that, within a large parameter range, does not depend on the charging parameters; (iv) The cluster Ising model and the long range SSH model, despite showing quantum phase transitions (QPTs) between states with orders dominated by different interaction ranges, do not exhibit super-extensive, i.e. more than linear in the number of sites, scaling of the charging power.

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引用次数: 0

Manifold-based multi-branch transfer learning for MI-EEG decoding 用于 MI-EEG 解码的基于 Manifold 的多分支转移学习

IF 5.3 1区数学 Q1 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS

Chaos Solitons & Fractals

Pub Date : 2025-04-08 DOI: 10.1016/j.chaos.2025.116326

Haoyu Li , Jianpeng An , Rongshun Juan , Tina P. Benko , Matjaž Perc , Weidong Dang , Zhongke Gao

We present a novel decoding approach for motor imagery electroencephalograms (MI-EEG) in Brain-Computer Interface (BCI) systems, aiming to advance neurorehabilitation and human–computer interaction. However, due to the non-stationary properties and low signal-to-noise ratio of MI-EEG, as well as significant individual variability, achieving accurate cross-subject decoding remains a challenge for real-world applications. To address this, we propose a manifold-based data processing method combined with a multi-branch network and enhanced by transfer learning to improve cross-subject performance. First, we identify the frequency bands relevant to motor imagery tasks and align multi-band data on the Symmetric Positive Definite (SPD) manifold using the Log-Euclidean Metric (LEM), including both full-band data and motor imagery-specific frequency bands. We then reconstruct these data from the manifold using a low-rank representation (LRP). Finally, we use a multi-branch network to extract and fuse deep features from the various frequency bands. We validated our approach on the BCI Competition IV-2a dataset and our JS-MI dataset, demonstrating that our method excels in cross-subject MI-EEG decoding tasks, with average classification accuracies of 74.55% and 71.94%, respectively. Our findings highlight the potential of this approach to improve BCI applications and facilitate more effective neurorehabilitation and human–computer interaction through enhanced MI-EEG decoding.

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