Article
Mathematics, Applied
Wentao Wang, Wei Chen
Summary: In this study, a class of stochastic inertial neural networks in random environments is proposed by introducing parameters perturbed by white noises. Mean-square exponential input-to-state stability is established on the model by constructing two Lyapunov-Krasovskii functionals, which generalizes recent results. An example with numerical simulation is conducted to support the theoretical findings.
ADVANCES IN DIFFERENCE EQUATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Junyi Wang, Zhanshan Wang, Xiangyong Chen, Jianlong Qiu
Summary: This paper investigates the synchronization problem of inertial neural networks with time-varying delays and generally Markovian jumping. Synchronization criteria and controllers are obtained using variable transformation method, Lyapunov-Krasovskii functionals, and linear matrix inequalities. Numerical examples confirm the effectiveness of the theoretical results.
Article
Mathematics, Applied
Suriguga, Yonggui Kao, Chuntao Shao, Xiangyong Chen
Summary: This paper investigates the mean square exponential stability of high-order Markovian jump reaction-diffusion HNNs with uncertain transition rates and time-varying delays using Lyapunov-Krasovskii functional method and LMI. The study shows that the known information of part of the transition rates can reveal the stability of the system. A numerical example is provided to illustrate the validity of the model.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Automation & Control Systems
Wenpin Luo, Jun Yang, Xinzhi Liu
Summary: This paper investigates the reliable H-infinity control on stochastic delayed Markovian jump systems with asynchronous jumped actuator failure and uncertain transition rates, establishing a generalized functional Ito's formula for the closed-loop systems and proposing a sufficient delay-dependent condition for controller design via matrix manipulation and relaxation method. An example on VTOL helicopter system is provided to demonstrate the feasibility and effectiveness of the proposed controller design scheme.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Mathematics, Applied
Xiaoqi Zhao, Lingzhen Dong
Summary: In this paper, the dynamic behaviors of a stochastic HIV model with the effect of treatment are studied using Ito's formula. The global positivity of the solution with positive initial value is discussed, and the limiting behavior of the solution is considered. The sufficient condition for the extinction of AIDS is obtained, and the unique ergodic stationary distribution of the solution is proven using an appropriate Lyapunov function. The validity of the results is illustrated through numerical simulations.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Physics, Multidisciplinary
T. Tamil Selvan, M. Kumar
Summary: The study of dynamics of epidemics, especially double epidemics, is highly important due to the increasing global warming and limited medical resources. This study focuses on an epidemic model with SIR and SIRS mechanisms. The local asymptotic stability and global stability of equilibrium points are proven using the Lyapunov function. The existence, extinction, and persistence of the stochastic system are also demonstrated. Numerical examples are provided to support the theoretical results.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2023)
Article
Mathematics
Zhengqi Ma, Shoucheng Yuan, Kexin Meng, Shuli Mei
Summary: This paper investigates the mean-square stability of uncertain time-delay stochastic systems driven by G-Brownian motion, which are commonly referred to as G-SDDEs. To derive a new set of sufficient stability conditions, we employ the linear matrix inequality (LMI) method and construct a Lyapunov-Krasovskii function under the constraint of uncertainty bounds. The resulting sufficient condition does not require any specific assumptions on the G-function, making it more practical. Additionally, we provide numerical examples to demonstrate the validity and effectiveness of the proposed approach.
Article
Mathematics, Applied
Jingjun Zhao, Yulian Yi, Yang Xu
Summary: This paper proposes two projected Euler type schemes for stochastic differential equations with Markovian switching and super-linear coefficients, and investigates their convergence under polynomial growth and monotone conditions. Furthermore, the convergence rates of these schemes for highly nonlinear equations with small noise are discussed. Numerical experiments are conducted to validate the theoretical results.
APPLIED MATHEMATICS AND COMPUTATION
(2021)
Article
Computer Science, Information Systems
Ning Zhang, Wenhai Qi, Ju H. Park, Huaicheng Yan, Jun Cheng
Summary: This paper studies sliding mode control (SMC) for discrete-time uncertain singular semi-Markovian jumping models. The goal is to establish stochastic admissibility conditions for the closed-loop system using strict linear matrix inequalities under the framework of the semi-Markovian jumping process. The paper designs a common sliding surface with a singular matrix to reduce the influence of repetitive jumping and numerical problems caused by the singular matrix. An improved reaching condition is used to synthesize the desired SMC mechanism and drive the system state onto the pre-designed sliding surface. The effectiveness of the proposed SMC approach is demonstrated using a DC motor model.
INFORMATION SCIENCES
(2023)
Article
Mathematics, Applied
Guangying Lv, Hongjun Gao, Jinlong Wei
Summary: This paper studies a stochastic process and introduces periodic solutions in a distributional sense. The definition of periodic solutions is given, and their existence on a bounded domain is established. Lastly, for cases where the probability density function exists, periodic solutions are obtained using deterministic partial differential equations.
JOURNAL OF EVOLUTION EQUATIONS
(2021)
Article
Automation & Control Systems
Junyi Wang, Zewen Ji, Hongli Xu, Jianlong Qiu, Yang Jiang
Summary: This article focuses on the finite-time sampled-data H infinity control problem of Markovian jumping linear systems with mode-dependent interval time-varying delays. Delay-dependent conditions for finite-time sampled-data control are obtained by using affine Bessel-Legendre inequality and appropriate mode-dependent Lyapunov-Krasovskii functional. Finally, the feasibility of the proposed method is demonstrated through two examples.
OPTIMAL CONTROL APPLICATIONS & METHODS
(2022)
Article
Automation & Control Systems
Jian Yang, Jinrong Wang, Michal Feckan
Summary: In this article, the mean-square consensus problem of multiagent systems with one leader and multiple followers is investigated. The uncertain disturbance from external environment or internal change of system is considered, and the interaction topology and time-varying delay are randomly regulated by a time-homogeneous Markovian chain. A distributed control protocol is designed based on the stochastic sampling information from neighbors and the leader. The sufficient condition to guarantee the mean-square consensus is concluded using stochastic Lyapunov theory and linear matrix inequality (LMI) approach. For the undirected topology case, a low-dimensional LMI-based consensus criterion is further derived based on the matrix diagonalization method. Finally, a numerical simulation is provided to demonstrate the reasonability of the theoretical results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Wentao Wang, Wei Chen
Summary: This study introduces a class of stochastic inertial neural networks in random environments, focusing on the concept of mean-square exponential stability. By establishing mean-square exponential stability using Lyapunov-Krasovskii functionals, the study extends and improves upon previous results, with numerical simulation provided as supporting evidence for the theoretical findings.
INTERNATIONAL JOURNAL OF CONTROL
(2022)
Article
Engineering, Multidisciplinary
Abhijit Majumder, Debadatta Adak, Nandadulal Bairagi
Summary: Deterministic mathematical models are commonly used to study predator-prey interactions for a better understanding of population dynamics. However, these models have limitations in capturing environmental noise and demographic stochasticity. This paper investigates a minimal deterministic model of phytoplankton-zooplankton interaction and compares its dynamics with stochastic versions formulated by two different techniques.
APPLIED MATHEMATICAL MODELLING
(2021)
Article
Computer Science, Artificial Intelligence
Linqi Wang, Jianwei Xia, Ju H. Park, Guoliang Chen, Xiangpeng Xie
Summary: This paper investigates the stochastic sampled-data exponential synchronization problem and the reachable set estimation problem for Markovian jump neural networks with time-varying delays and external disturbances. The proposed approach constructs a mode-dependent two-sided loop based Lyapunov functional and derives the conditions for the mean square exponential stability of the error system. A mode-dependent stochastic sampled-data controller and a stochastic sampled-data controller with RSE are designed. Numerical examples and a resistor-capacitor network circuit demonstrate the effectiveness of the proposed approach in obtaining larger sampled-data periods compared to existing methods.
Article
Automation & Control Systems
Xianghui Zhou, Xin Wang, Jinde Cao, Zizong Yan
Summary: This paper focuses on the synchronization control of Stochastic Neural Networks (SNNs) with Time-Varying Delays (TVD) based on the stability of the error system. The output result analysis of networks based on a logic framework is carried out to observe the effect of the slave system following the drive system. The gain matrix of the controller with index regulator is designed to adjust the intensity of the parameters for achieving efficient control of the error system. The proposed control method is superior to the control approach given by comparative literature, and the exponential synchronous conditions are obtained based on trace similarity and the Lyapunov stability principle.
EUROPEAN JOURNAL OF CONTROL
(2023)
Article
Acoustics
Yiping Luo, Xitong Gao, Jinde Cao, Ardak Kashkynbayev
Summary: This study investigates the event-triggered consensus problem for observer-based second-order leader-following heterogeneous multi-agent systems with nonlinear term delay under input saturation conditions. The observer is designed to reconstruct the system state and achieve the required state feedback. By combining saturation control and event-triggered pinning control, multi-agent consensus is achieved. The Lyapunov stability theory, algebraic Riccati equation, matrix theory, and other analytical techniques are used to obtain the sufficient conditions for consensus. The proposed event-triggered function avoids Zeno behavior, and the feasibility of the results is verified through numerical simulation.
JOURNAL OF VIBRATION AND CONTROL
(2023)
Article
Engineering, Multidisciplinary
Xiaoying Chen, Yang Liu, Qihua Ruan, Jinde Cao
Summary: This paper studies the stabilization of nonlinear time-delay systems under flexible delayed impulsive control. It provides sufficient conditions for establishing stability property using exponential Lyapunov-Razumikhin functions. The results show that the size of delay in continuous dynamics can be flexible, and there is no magnitude relationship between the delay in continuous flow and impulsive delay. By utilizing the proposed method of average impulsive estimation (AIE), the rate coefficients can be adjusted flexibly, and the impulsive delay can be integrated to ensure the stabilization effect of impulses.
APPLIED MATHEMATICAL MODELLING
(2023)
Article
Engineering, Biomedical
Gucheng Zhang, Rencan Nie, Jinde Cao, Luping Chen, Ya Zhu
Summary: This research proposes a novel end-to-end unsupervised learning fusion network called FDGNet to address the insufficient complementary feature extraction and luminance degradation in multimodal medical image fusion. The network utilizes feature-weighted guided learning to extract complementary features and generate interactive weights for direct fusion. A hybrid loss composed of weighted fidelity loss and feature difference loss is introduced to effectively train the network. Experimental results show that FDGNet preserves rich details from source images and outperforms other algorithms in quantitative metrics.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Article
Engineering, Multidisciplinary
Ning Li, JinDe Cao
Summary: This study investigates the issue of bipartite quasi-synchronization in coupled networks with general cooperative-competitive topology and event-triggered communications. The study extends the network topology to a more general signed network where antagonistic interactions can exist within or across subgroups. By utilizing stochastic Lyapunov stability analysis, the study provides criteria for bipartite quasi-synchronization in structurally unbalanced networks and also bounds the synchronization error. Theoretical results are verified through simulations.
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
(2023)
Article
Automation & Control Systems
Tao Wen, Jinde Cao, Kang Hao Cheong
Summary: The usage of social media is growing worldwide, but the existence of community structure makes social networks vulnerable to attacks and large-scale losses. To evaluate community vulnerability, a gravity-based model is designed, which considers multiple information sources. The model uses a fuzzy ranking algorithm and Sobol' indices to analyze vulnerability relationships and weighting parameters. Experimental tests demonstrate that the model can be used to identify vulnerable components in real-time network situations.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Electrical & Electronic
Yiheng Wei, Linlin Zhao, Junguo Lu, Fawaz E. Alsaadi, Jinde Cao
Summary: This study systematically explores the stability of delta delay fractional order systems with an extra order, addresses the approximation of stable region and the derivation of relevant LMI conditions caused by the complicated stable region. The proposed stability conditions are formulated in terms of LMIs and the validity and applicability of the approaches are demonstrated by simulation study.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS
(2023)
Article
Automation & Control Systems
Shanshan Zhao, Haiyang Zhang, Lianglin Xiong, Shiping Wen, Jinde Cao, Yi Zhang
Summary: This paper studies the resilient adaptive event-triggered synchronization control problem for a class of Piecewise-Homogeneous Uncertain Markov Jump Neural Networks (PHUMJNNs) with time-varying delays under the aperiodic Denial-of-service (DoS) attacks. It proposes a new way of carving DoS attacks based on fixed detection periods and designs a Resilient Adaptive Event-triggered Communication (RAETC) method for sensor and controller. The paper also introduces a single functional and a looped functional to construct the Lyapunov-Krasovskii functional, and obtains the exponential mean square stabilization criterion for the error system using the input delay method and the linear matrix inequality technique.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Jiajin He, Min Xiao, Jing Zhao, Zhengxin Wang, Yi Yao, Jinde Cao
Summary: The influence of network topology on the response dynamics of neural networks is still not completely understood. Understanding the relationship between topological structures and dynamics is crucial for understanding brain function. In this study, a new diffusion neural network model with a binary tree structure and multiple delays was proposed to explore the role of topological structures in the response dynamic. A novel full-dimensional nonlinear state feedback control strategy was also introduced to optimize relevant neurodynamics. The effectiveness of the proposed control strategy was demonstrated through numerical examples and comparative experiments.
Article
Physics, Multidisciplinary
Yuwei Yang, Zhuoxuan Li, Jun Chen, Zhiyuan Liu, Jinde Cao
Summary: This paper proposes an extreme learning machine (ELM) algorithm based on residual correction and Tent chaos sequence (TRELM-DROP) for accurate prediction of traffic flow. The algorithm reduces the impact of randomness in traffic flow through the Tent chaos strategy and residual correction method, and avoids weight optimization using the iterative method. A DROP strategy is introduced to improve the algorithm's ability to predict traffic flow under varying conditions.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2024)
Article
Automation & Control Systems
Xiangwei Bu, Maolong Lv, Humin Lei, Jinde Cao
Summary: This paper proposes a fuzzy-neural-approximation-based pseudo nonaffine control protocol for waverider vehicles (WVs), which can guarantee tracking errors with the desired prescribed performance and reject the obstacle of fragility inherent to the traditional prescribed performance control (PPC). The pseudo control approximates the nonaffine dynamics of WVs without the need for model affinization. Fuzzy neural approximators are combined with an adaptive compensation strategy to withstand system uncertainties and external disturbances. A new type of nonfragile prescribed performance is proposed to remedy the fragility defect associated with existing PPC.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Electrical & Electronic
Chaozhen Ma, Rencan Nie, Hongwei Ding, Jinde Cao, Jiatian Mei
Summary: This article proposes a method for infrared and visible image fusion based on fractional-order variation with convolution norm. The method utilizes convolution norm to extract structural features of infrared and visible images, alleviating residual errors, and employs fractional-order variation instead of total variation to preserve more details and avoid the staircase effect. A focused term is also introduced to prevent luminance degradation of the fusion result. Experimental results demonstrate that the proposed method achieves better performance in subjective and objective evaluation compared to other excellent methods.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Mathematics, Applied
Wenjie Li, Yajuan Guan, Jinde Cao, Fei Xu
Summary: This article establishes the global stability of the disease-free equilibrium in a degenerate diffusion system involving environmental transmission and spatial heterogeneity. It provides important insights into the transmission dynamics of avian influenza virus among avian, poultry, and human populations.
APPLIED MATHEMATICS LETTERS
(2024)
Article
Computer Science, Artificial Intelligence
Chengdai Huang, Heng Liu, Tingwen Huang, Jinde Cao
Summary: This article explores the bifurcations in a fractional-order neutral-type neural network with two nonidentical delays, demonstrating the stability performance with a smaller time delay and comparing it with integer-order neural networks. The effects of coefficients and time delay on bifurcation points are analyzed, and the superiority of fractional-order delayed neural network is highlighted. Neglecting the reverberations of neutral delays can lead to inaccurate stability results. Numerical experiments validate the findings.
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Hanjie Liu, Jinde Cao, Wei Huang, Xinli Shi, Xingye Zhou, Zhuoxuan Li
Summary: A data-driven multidimensional framework is proposed to evaluate pavement condition by utilizing multilayer network representation learning. The method can capture the nonlinear interactions among performance attributes and provide a more in-depth understanding of pavement service condition. Experimental results demonstrate the effectiveness of this method in multi-attribute evaluation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
