In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of t...In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of the considered neural networks with more relaxed conditions imposed on the amplification functions is analyzed by using set-valued mapping and Kakutani's fixed point theorem,which has rarely been used to study such problem.Secondly,the fixed-time synchronization of the error system of the considered neural networks is also investigated by designing a novel control strategy,which can improve not only the previous ones with sign function greatly,but also can reduce the chattering phenomenon.Finally,two numerical examples are presented to further illustrate the validity of the obtained results.展开更多
This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of ...This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of FxTS is independent of the initial values and parameters of the CNs,a modified fixed-time(FxT)stability theorem is proposed,where the ST is determined by an arbitrary positive number given in advance.Then,continuous controller and discontinuous controller are designed to realize the modified FxTS target of CNs.In addition,based on the designed controllers,CNs can achieve synchronization at any given time,or even earlier.And control strategies effectively solve the problem of ST related to the parameters of CNs.Finally,an appropriate simulation example is conducted to examine the effectiveness of the designed control strategies.展开更多
Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this paper.Both continuous and discontinuous activations are considered forMNNs.And the mixed...Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this paper.Both continuous and discontinuous activations are considered forMNNs.And the mixed delays which are closer to reality are taken into the system.Besides,two kinds of control schemes are proposed,including feedback and adaptive control strategies.Based on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are acquired.Moreover,the upper bound of settling time(ST)which is independent of the initial values is given.Finally,the feasibility of our theory is attested by simulation examples.展开更多
A novel feedback control is proposed to investigate the stochastic finite-time/fixed-time synchronization between two stochas-tic coupled nonlinear systems(SCNSs).Based on graph theory and Lyapunov function methods,so...A novel feedback control is proposed to investigate the stochastic finite-time/fixed-time synchronization between two stochas-tic coupled nonlinear systems(SCNSs).Based on graph theory and Lyapunov function methods,some effective stochastic finite-time/fixed-time synchronization criteria for SCNSs are established.Finally,the examples are included to demonstrate our analytical results.展开更多
Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are ...Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are proposed to overcome the difficulty of dealing with fixedtime stability/synchronization of CNs for AIC.展开更多
In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronizat...In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronization of considered networks via introducing two types of controllers and employing some inequality techniques. Lastly, our theoretical results are verified via giving two numerical examples with their Matlab simulations.展开更多
This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,i...This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.展开更多
This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays(mixed delays). First, by constructing a proper variable substi...This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays(mixed delays). First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as a first-order differential system. Second, by constructing Lyapunov functions and using differential inequalities,some new and effective criteria are obtained for ensuring the finite-time synchronization. Finally, three numerical examples are also given at the end of this paper to show the effectiveness of the results.展开更多
This paper investigates the fixed-time synchronization problem of complex networks.A novel switching controller is proposed to solve the problem.The designed controller in this paper only needs intermittently to pin a...This paper investigates the fixed-time synchronization problem of complex networks.A novel switching controller is proposed to solve the problem.The designed controller in this paper only needs intermittently to pin a few of nodes,which could reduce the control time and save the system’s energy.Moreover,compared with the existing control methods for the fixed-time synchronization,the novel controller does not use the sign function,which could avoid the chattering behaviors.By constructing a Lyapunov function and designing a comparison system,some sufficient conditions are obtained to achieve the fixed-time synchronization.Finally,the numerical simulations could verify the effectiveness and feasibility of the proposed control approaches.展开更多
Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and ...Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and inadequate modeling of image details.To address these limitations,a comprehensively optimized lip synchronization framework extending the Wav2Lip architecture was proposed in this study.Firstly,based on the Wav2Lip model,a facial region extraction strategy using facial keypoints was designed,which effectively enhances the robustness of facial alignment during lip synchronization for digital virtual humans.Then,a cross-modal attention fusion module between visual and speech features was introduced to improve cross-modal information fusion,and a dynamic receptive field convolution module was developed in the generation branch to enhance the modeling performance of the lip region.Finally,experiments were conducted on the VFHQ dataset.The proposed method was compared with Wav2Lip,VideoRetalking,and DI-Net models,and its performance was evaluated using three metrics:LSE-C,CSIM,and FID.Experimental results showed that the proposed method achieves significant improvements in synchronization accuracy and image fidelity,providing an efficient and feasible solution for lip-synthesis tasks of digital virtual humans.展开更多
This paper presents an adaptive multi-agent coordination(AMAC)strategy suitable for complex scenarios,which only requires information exchange between neighbouring robots.Unlike traditional multi-agent coordination me...This paper presents an adaptive multi-agent coordination(AMAC)strategy suitable for complex scenarios,which only requires information exchange between neighbouring robots.Unlike traditional multi-agent coordination methods that are solved by neural dynamics,the proposed strategy displays greater flexibility,adaptability and scalability.Furthermore,the proposed AMAC strategy is reconstructed as a time-varying complex-valued matrix equation.By introducing a dynamic error function,a fixed-time convergent zeroing neural network(FTCZNN)model is designed for the online solution of the AMAC strategy,with its convergence time upper bound derived theoretically.Finally,the effectiveness and applicability of the coordination control method are demonstrated by numerical simulations and physical experiments.Numerical results indicate that this method can reduce the formation error to the order of 10^(-6)within 1.8 s.展开更多
Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this fie...Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this field has focused on systems in equilibrium or steady states.In this work,we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization.展开更多
This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact ...This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.展开更多
In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this pap...In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this paper,these influences are investigated from the perspective of the time domain.First,a novel time-domain model of the multi-VSC system is obtained by using a multi-scale method.On this basis,a stability criterion is proposed to assess the synchronization stability of the system.Then,the accuracy of the time-domain model and its stability criterion in various conditions are discussed.Moreover,the negative impact of the interaction on the system is quantified.Finally,the above theoretical analysis is also verified in the controller hardware-in-the-loop(CHIL)experiments.展开更多
Neuromorphic circuits based on superconducting tunnel junctions have attracted much attention due to their highspeed computing capabilities and low energy consumption.Josephson junction circuits can effectively mimic ...Neuromorphic circuits based on superconducting tunnel junctions have attracted much attention due to their highspeed computing capabilities and low energy consumption.Josephson junction circuits can effectively mimic biological neural dynamics.Leveraging these advantages,we construct a Josephson junction neuron-like model with a phasedependent dissipative current,referred to as a memristive current.The proposed memristive Josephson junction model exhibits complex dynamical behaviors.Furthermore,considering the effect of a fast-modulated synapse,we explore synchronization phenomena in coupled networks under varying coupling conductances and excitatory/inhibitory interactions.Finally,we extend the neuromorphic Josephson junction model—exhibiting complex dynamics—to the field of image encryption.These results not only enrich the understanding of the dynamical characteristics of memristive Josephson junctions but also provide a theoretical basis and technical support for the development of new neural networks and their applications in information security technology.展开更多
A novel aperiodically intermittent impulse control(AIIC)method is proposed to investigate the exponential synchronization in mean square(ESMS)of a class of impulsive stochastic infinite-dimensional systems with Poisso...A novel aperiodically intermittent impulse control(AIIC)method is proposed to investigate the exponential synchronization in mean square(ESMS)of a class of impulsive stochastic infinite-dimensional systems with Poisson jumps(ISIDSP).The AIIC control strategy inherits the flexibility of aperiodically intermittent control,including the variable control period,adjustable control interval length,and the discretization of impulsive control.In addition,this article introduces a novel mild Itô's formula.By leveraging semigroup theory,the contraction mapping principle,and graph theory,along with constructing the Lyapunov function,the criterion for the existence and uniqueness of a mild solution of ISIDSP is thereby established.Furthermore,the mean-square exponential synchronization problem of the above systems is resolved,and the constraints within the mild solution domain are alleviated.These criteria clarify the impact of control parameters,control intervals and network topology on ESMS.The theoretical results are subsequently applied to a class of neural networks with reaction-diffusion processes,and the validity of the results is verified using numerical simulations.展开更多
This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to es...This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to estimate higher-order synchronization errors,enabling the controller to rely solely on relative output measurements.This approach significantly reduces the dependence on full-state information,which is often infeasible or costly in practical engineering applications.An output feedback control strategy is developed to overcome these limitations while ensuring robust and effective synchronization.Simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the theoretical findings.展开更多
Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchroniza...Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.展开更多
Federated Learning(FL)has become a leading decentralized solution that enables multiple clients to train a model in a collaborative environment without directly sharing raw data,making it suitable for privacy-sensitiv...Federated Learning(FL)has become a leading decentralized solution that enables multiple clients to train a model in a collaborative environment without directly sharing raw data,making it suitable for privacy-sensitive applications such as healthcare,finance,and smart systems.As the field continues to evolve,the research field has become more complex and scattered,covering different system designs,training methods,and privacy techniques.This survey is organized around the three core challenges:how the data is distributed,how models are synchronized,and how to defend against attacks.It provides a structured and up-to-date review of FL research from 2023 to 2025,offering a unified taxonomy that categorizes works by data distribution(Horizontal FL,Vertical FL,Federated Transfer Learning,and Personalized FL),training synchronization(synchronous and asynchronous FL),optimization strategies,and threat models(data leakage and poisoning attacks).In particular,we summarize the latest contributions in Vertical FL frameworks for secure multi-party learning,communication-efficient Horizontal FL,and domain-adaptive Federated Transfer Learning.Furthermore,we examine synchronization techniques addressing system heterogeneity,including straggler mitigation in synchronous FL and staleness management in asynchronous FL.The survey covers security threats in FL,such as gradient inversion,membership inference,and poisoning attacks,as well as their defense strategies that include privacy-preserving aggregation and anomaly detection.The paper concludes by outlining unresolved issues and highlighting challenges in handling personalized models,scalability,and real-world adoption.展开更多
In this paper,the fixed-time outer synchronization of complex networks with noise coupling is investigated.Based on the theory of fixed-time stability and matrix inequalities,sufficient conditions for fixed-time outer...In this paper,the fixed-time outer synchronization of complex networks with noise coupling is investigated.Based on the theory of fixed-time stability and matrix inequalities,sufficient conditions for fixed-time outer synchronization are established and the estimation of the upper bound of the setting time is obtained.The result shows that the setting time can be adjusted to a desired value regardless of the initial states.Numerical simulations are performed to verify the effectiveness of the theoretical results.The effects of control parameters and the density of controlled nodes on the converging time are studied.展开更多
基金Supported by the National Natural Science Foundation of China(62576008)University Annual Scientific Research Plan of Anhui Province(2022AH030023)。
文摘In this paper,a class of discontinuous Cohen-Grossberg neural networks with timevarying delays is considered.Firstly,under the extended Filippov differential inclusions framework,the problem of periodic solutions of the considered neural networks with more relaxed conditions imposed on the amplification functions is analyzed by using set-valued mapping and Kakutani's fixed point theorem,which has rarely been used to study such problem.Secondly,the fixed-time synchronization of the error system of the considered neural networks is also investigated by designing a novel control strategy,which can improve not only the previous ones with sign function greatly,but also can reduce the chattering phenomenon.Finally,two numerical examples are presented to further illustrate the validity of the obtained results.
基金Supported by the National Natural Science Foundation of China(62476082)。
文摘This paper investigates modified fixed-time synchronization(FxTS)of complex networks(CNs)with time-varying delays based on continuous and discontinuous controllers.First,for the sake of making the settling time(ST)of FxTS is independent of the initial values and parameters of the CNs,a modified fixed-time(FxT)stability theorem is proposed,where the ST is determined by an arbitrary positive number given in advance.Then,continuous controller and discontinuous controller are designed to realize the modified FxTS target of CNs.In addition,based on the designed controllers,CNs can achieve synchronization at any given time,or even earlier.And control strategies effectively solve the problem of ST related to the parameters of CNs.Finally,an appropriate simulation example is conducted to examine the effectiveness of the designed control strategies.
基金supported by National Natural Science Foundation of China under(Grant Nos.62173175,12026235,12026234,61903170,11805091,61877033,61833005)by 111 Project under Grant B17040+2 种基金by the Natural Science Foundation of Shandong Province under Grant Nos.ZR2019BF045,ZR2019MF021,ZR2019QF004by the Project of Shandong Province Higher Educational Science and Technology Program No.J18KA354by the Key Research and Development Project of Shandong Province of China,No.2019GGX101003.
文摘Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this paper.Both continuous and discontinuous activations are considered forMNNs.And the mixed delays which are closer to reality are taken into the system.Besides,two kinds of control schemes are proposed,including feedback and adaptive control strategies.Based on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are acquired.Moreover,the upper bound of settling time(ST)which is independent of the initial values is given.Finally,the feasibility of our theory is attested by simulation examples.
文摘A novel feedback control is proposed to investigate the stochastic finite-time/fixed-time synchronization between two stochas-tic coupled nonlinear systems(SCNSs).Based on graph theory and Lyapunov function methods,some effective stochastic finite-time/fixed-time synchronization criteria for SCNSs are established.Finally,the examples are included to demonstrate our analytical results.
基金supported in part by the Natural Science Foundation of Jiangsu Province of China(BK20220811,BK20202006)the National Natural Science Foundation of China(62203114,62273094)+3 种基金the Fundamental Research Funds for the Central Universitiesthe“Zhishan”Scholars Programs of South-east UniversityChina Postdoctoral Science Foundation(2022M 710684)Excellent Postdoctoral Foundation of Jiangsu Province of China(2022ZB116)。
文摘Dear Editor, This letter deals with fixed-time synchronization(Fd-TS) of complex networks(CNs) under aperiodically intermittent control(AIC)for the first time. The average control rate and a new Lyapunov function are proposed to overcome the difficulty of dealing with fixedtime stability/synchronization of CNs for AIC.
文摘In this paper, fixed-time (FXT) synchronization issue of a type of neural networks (NNs) with stochastic perturbations is considered. First, we obtained some novel sufficient criteria to guarantee the FXT synchronization of considered networks via introducing two types of controllers and employing some inequality techniques. Lastly, our theoretical results are verified via giving two numerical examples with their Matlab simulations.
基金supported by the National Natural Science Foundation of China(62373317)the Tianshan Talent Training Program(2022TSYCCX0013)+3 种基金the Key Project of Natural Science Foundation of Xinjiang(2021D01D10)the Basic Research Foundation for Universities of Xinjiang(XJEDU2023P023)the Xinjiang Key Laboratory of Applied Mathematics(XJDX1401)the Intelligent Control and Optimization Research Platform in Xinjiang University.
文摘This paper is dedicated to fixed-time passivity and synchronization for multi-weighted spatiotemporal directed networks.First,to achieve fixed-time passivity,a type of decentralized power-law controller is developed,in which only one parameter needs to be adjusted in the power-law terms;this greatly decreases the inconvenience of parameter adjustment.Second,several fixed-time passivity criteria with LMI forms are derived by using a Gauss divergence theorem to deal with the spatial diffusion of nodes and by applying the Hölder’s inequality to dispose rigorously the power-law term greater than one in the designed control scheme;this improves the previous theoretical analysis.Additionally,the fixed-time synchronization of spatiotemporal directed networks with multi-weights is addressed as a direct result of fixed-time strict passivity.Finally,a numerical example is presented in order to show the validity of the theoretical analysis.
文摘This paper considers the drive-response synchronization in finite-time and fixed-time of inertial neural networks with time-varying and distributed delays(mixed delays). First, by constructing a proper variable substitution, the original inertial neural networks can be rewritten as a first-order differential system. Second, by constructing Lyapunov functions and using differential inequalities,some new and effective criteria are obtained for ensuring the finite-time synchronization. Finally, three numerical examples are also given at the end of this paper to show the effectiveness of the results.
基金supported in part by the National Social Science Fund under Grant No.18BTJ025in part by the Scientific Research Starting Project of SWPU under Grant No.2019QHZ018in part by the Youth Innovation Team of SWPU under Grant No.2019CXTD08。
文摘This paper investigates the fixed-time synchronization problem of complex networks.A novel switching controller is proposed to solve the problem.The designed controller in this paper only needs intermittently to pin a few of nodes,which could reduce the control time and save the system’s energy.Moreover,compared with the existing control methods for the fixed-time synchronization,the novel controller does not use the sign function,which could avoid the chattering behaviors.By constructing a Lyapunov function and designing a comparison system,some sufficient conditions are obtained to achieve the fixed-time synchronization.Finally,the numerical simulations could verify the effectiveness and feasibility of the proposed control approaches.
文摘Lip synchronization serves as a core technology for enabling natural interactions in digital virtual humans.However,it faces challenges such as insufficient dynamic correspondence between speech and lip movements and inadequate modeling of image details.To address these limitations,a comprehensively optimized lip synchronization framework extending the Wav2Lip architecture was proposed in this study.Firstly,based on the Wav2Lip model,a facial region extraction strategy using facial keypoints was designed,which effectively enhances the robustness of facial alignment during lip synchronization for digital virtual humans.Then,a cross-modal attention fusion module between visual and speech features was introduced to improve cross-modal information fusion,and a dynamic receptive field convolution module was developed in the generation branch to enhance the modeling performance of the lip region.Finally,experiments were conducted on the VFHQ dataset.The proposed method was compared with Wav2Lip,VideoRetalking,and DI-Net models,and its performance was evaluated using three metrics:LSE-C,CSIM,and FID.Experimental results showed that the proposed method achieves significant improvements in synchronization accuracy and image fidelity,providing an efficient and feasible solution for lip-synthesis tasks of digital virtual humans.
基金supported by the National Natural Science Foundation of China under Grants 61962023,61562029 and 62466019.
文摘This paper presents an adaptive multi-agent coordination(AMAC)strategy suitable for complex scenarios,which only requires information exchange between neighbouring robots.Unlike traditional multi-agent coordination methods that are solved by neural dynamics,the proposed strategy displays greater flexibility,adaptability and scalability.Furthermore,the proposed AMAC strategy is reconstructed as a time-varying complex-valued matrix equation.By introducing a dynamic error function,a fixed-time convergent zeroing neural network(FTCZNN)model is designed for the online solution of the AMAC strategy,with its convergence time upper bound derived theoretically.Finally,the effectiveness and applicability of the coordination control method are demonstrated by numerical simulations and physical experiments.Numerical results indicate that this method can reduce the formation error to the order of 10^(-6)within 1.8 s.
基金supported by the National Natural Science Foundation of China (Grant No.12274131)the Innovation Program for Quantum Science and Technology (Grant No.2024ZD0300101)。
文摘Optical non-reciprocity is a fundamental phenomenon in photonics.It is crucial for developing devices that rely on directional signal control,such as optical isolators and circulators.However,most research in this field has focused on systems in equilibrium or steady states.In this work,we demonstrate a room-temperature Rydberg atomic platform where the unidirectional propagation of light acts as a switch to mediate time-crystalline-like collective oscillations through atomic synchronization.
基金supported by National Natural Science Foundation of China[grant number 62173208]Taishan Scholar Project of Shandong Province of China[grant number tsqn202103061]。
文摘This paper is dedicated to solving the problem of adaptive fuzzy fault-tolerant tracking control for a class of time-varying high-order uncertain nonlinear systems.The motivation comes from how to construct a compact set large enough in which the approximation of any unknown continuous function by a fuzzy logic system(FLS)is effective while compensating sensor/actuator faults and external disturbances.The difficulty is to verify the boundedness of closed-loop signals on the constructed compact set and to reduce the number of the variables of the fuzzy membership functions as many as possible.By a new lemma,linear/nonlinear terms are introduced in adaptive laws to dominate unknown residual terms.With adding a power integrator method,a unified fault-tolerant controller is designed to drive the tracking error to converge to a small compact set of the origin within a fixed time,regardless of whether the system suffers from faults and disturbances.Superior to the existing results,in the presence of time-varying factors the scheme of this paper clarifies the logical relationship between the compactness of the approximation and the boundedness of the state variables.Finally,the application of control strategy is demonstrated by numerical/practical examples.
基金supported by the Science and Technology Project of State Grid Corporation of China(5400-202199281A-0-0-00).
文摘In a multiple voltage source converter(VSC)system,the nonlinear characteristics of phase-locked loops(PLLs)and their interactions have a significant influence on the synchronization stability of converters.In this paper,these influences are investigated from the perspective of the time domain.First,a novel time-domain model of the multi-VSC system is obtained by using a multi-scale method.On this basis,a stability criterion is proposed to assess the synchronization stability of the system.Then,the accuracy of the time-domain model and its stability criterion in various conditions are discussed.Moreover,the negative impact of the interaction on the system is quantified.Finally,the above theoretical analysis is also verified in the controller hardware-in-the-loop(CHIL)experiments.
基金supported by the National Natural Science Foundation of China(Grant No.12302070)the Natural Science Foundation of Ningxia(Grant No.2024AAC05002)+1 种基金the Youth Science and Technology Talent Cultivation Project of Ningxiathe Ningxia Science and Technology Leading Talent Training Program(Grant No.2022GKLRLX04)。
文摘Neuromorphic circuits based on superconducting tunnel junctions have attracted much attention due to their highspeed computing capabilities and low energy consumption.Josephson junction circuits can effectively mimic biological neural dynamics.Leveraging these advantages,we construct a Josephson junction neuron-like model with a phasedependent dissipative current,referred to as a memristive current.The proposed memristive Josephson junction model exhibits complex dynamical behaviors.Furthermore,considering the effect of a fast-modulated synapse,we explore synchronization phenomena in coupled networks under varying coupling conductances and excitatory/inhibitory interactions.Finally,we extend the neuromorphic Josephson junction model—exhibiting complex dynamics—to the field of image encryption.These results not only enrich the understanding of the dynamical characteristics of memristive Josephson junctions but also provide a theoretical basis and technical support for the development of new neural networks and their applications in information security technology.
基金supported in part by the National Natural Science Foundation of China(12471422,62573274,12371173)the Natural Science Foundation of Shandong Province of China(ZR2022LLZ003,ZR2024MF001)the Funding for Visiting Studies and Research by Teachers in Ordinary Undergraduate Colleges and Universities in Shandong Province。
文摘A novel aperiodically intermittent impulse control(AIIC)method is proposed to investigate the exponential synchronization in mean square(ESMS)of a class of impulsive stochastic infinite-dimensional systems with Poisson jumps(ISIDSP).The AIIC control strategy inherits the flexibility of aperiodically intermittent control,including the variable control period,adjustable control interval length,and the discretization of impulsive control.In addition,this article introduces a novel mild Itô's formula.By leveraging semigroup theory,the contraction mapping principle,and graph theory,along with constructing the Lyapunov function,the criterion for the existence and uniqueness of a mild solution of ISIDSP is thereby established.Furthermore,the mean-square exponential synchronization problem of the above systems is resolved,and the constraints within the mild solution domain are alleviated.These criteria clarify the impact of control parameters,control intervals and network topology on ESMS.The theoretical results are subsequently applied to a class of neural networks with reaction-diffusion processes,and the validity of the results is verified using numerical simulations.
文摘This paper addresses the synchronization of follower agents’state vectors with that of a leader in high-order nonlinear multi-agent systems.The proposed low-complexity control scheme employs high-gain observers to estimate higher-order synchronization errors,enabling the controller to rely solely on relative output measurements.This approach significantly reduces the dependence on full-state information,which is often infeasible or costly in practical engineering applications.An output feedback control strategy is developed to overcome these limitations while ensuring robust and effective synchronization.Simulation results are provided to demonstrate the effectiveness of the proposed approach and validate the theoretical findings.
文摘Clock synchronization has important applications in multi-agent collaboration(such as drone light shows,intelligent transportation systems,and game AI),group decision-making,and emergency rescue operations.Synchronization method based on pulse-coupled oscillators(PCOs)provides an effective solution for clock synchronization in wireless networks.However,the existing clock synchronization algorithms in multi-agent ad hoc networks are difficult to meet the requirements of high precision and high stability of synchronization clock in group cooperation.Hence,this paper constructs a network model,named DAUNet(unsupervised neural network based on dual attention),to enhance clock synchronization accuracy in multi-agent wireless ad hoc networks.Specifically,we design an unsupervised distributed neural network framework as the backbone,building upon classical PCO-based synchronization methods.This framework resolves issues such as prolonged time synchronization message exchange between nodes,difficulties in centralized node coordination,and challenges in distributed training.Furthermore,we introduce a dual-attention mechanism as the core module of DAUNet.By integrating a Multi-Head Attention module and a Gated Attention module,the model significantly improves information extraction capabilities while reducing computational complexity,effectively mitigating synchronization inaccuracies and instability in multi-agent ad hoc networks.To evaluate the effectiveness of the proposed model,comparative experiments and ablation studies were conducted against classical methods and existing deep learning models.The research results show that,compared with the deep learning networks based on DASA and LSTM,DAUNet can reduce the mean normalized phase difference(NPD)by 1 to 2 orders of magnitude.Compared with the attention models based on additive attention and self-attention mechanisms,the performance of DAUNet has improved by more than ten times.This study demonstrates DAUNet’s potential in advancing multi-agent ad hoc networking technologies.
文摘Federated Learning(FL)has become a leading decentralized solution that enables multiple clients to train a model in a collaborative environment without directly sharing raw data,making it suitable for privacy-sensitive applications such as healthcare,finance,and smart systems.As the field continues to evolve,the research field has become more complex and scattered,covering different system designs,training methods,and privacy techniques.This survey is organized around the three core challenges:how the data is distributed,how models are synchronized,and how to defend against attacks.It provides a structured and up-to-date review of FL research from 2023 to 2025,offering a unified taxonomy that categorizes works by data distribution(Horizontal FL,Vertical FL,Federated Transfer Learning,and Personalized FL),training synchronization(synchronous and asynchronous FL),optimization strategies,and threat models(data leakage and poisoning attacks).In particular,we summarize the latest contributions in Vertical FL frameworks for secure multi-party learning,communication-efficient Horizontal FL,and domain-adaptive Federated Transfer Learning.Furthermore,we examine synchronization techniques addressing system heterogeneity,including straggler mitigation in synchronous FL and staleness management in asynchronous FL.The survey covers security threats in FL,such as gradient inversion,membership inference,and poisoning attacks,as well as their defense strategies that include privacy-preserving aggregation and anomaly detection.The paper concludes by outlining unresolved issues and highlighting challenges in handling personalized models,scalability,and real-world adoption.
基金Supported by the National Natural Science Foundation of China under Grant Nos.11711530203 and 11771443the Fundamental Research Funds for the Central Universities under Grant No.2015XKMS076
文摘In this paper,the fixed-time outer synchronization of complex networks with noise coupling is investigated.Based on the theory of fixed-time stability and matrix inequalities,sufficient conditions for fixed-time outer synchronization are established and the estimation of the upper bound of the setting time is obtained.The result shows that the setting time can be adjusted to a desired value regardless of the initial states.Numerical simulations are performed to verify the effectiveness of the theoretical results.The effects of control parameters and the density of controlled nodes on the converging time are studied.
