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Yaning Yu et al.
Summary: This article focuses on the pinning synchronization and adaptive synchronization problems of complex-valued inertial neural networks with time-varying delays in fixed-time intervals. It proposes a new pinning controller and an adaptive controller to ensure the fixed-time stability and adaptive fixed-time stability of the closed-loop error system, respectively. The effectiveness of the proposed methods is verified through numerical examples.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Yuan Shen et al.
Summary: This paper proposes a new approach to the synchronization problem of complex-valued neural networks via event-triggered pinning impulsive control (ETPIC), with delay-dependent synchronization criteria derived using Lyapunov functional method and differential inequality technique. Numerical examples demonstrate the effectiveness of the theoretical results.
Article
Computer Science, Artificial Intelligence
Changqing Long et al.
Summary: This article focuses on the issue of finite-time stabilization of complex-valued neural networks with proportional delays and inertial terms. It directly constructs Lyapunov functions without separating the original complex-valued neural networks into two real-valued subsystems. The article introduces intermediate variables to transform the complex-valued inertial neural networks into first-order differential equation form, and establishes new criteria under the finite-time stability theory to ensure the finite-time stabilizability of the networks using a newly designed complex-valued feedback controller. An adaptive control strategy is also proposed to reduce control expenses. Numerical examples are provided to demonstrate the validity of the results.
Article
Engineering, Multidisciplinary
Xinrui Ji et al.
Summary: This paper investigates the synchronization of coupled neural networks using distributed delayed impulsive control. It proposes the concept of average delayed impulsive weight and extends the comparison principle to consider delayed impulses. Sufficient conditions for global exponential synchronization are obtained, and the convergence rate is estimated.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Theory & Methods
Xiaofan Li et al.
Summary: This paper considers a new class of fuzzy inertial complex-valued neural networks with state-dependent coefficients and mixed delays. The model is constructed and converted into two real-valued neural networks. Novel adaptive controller and synchronization criteria are designed and verified through theoretical analysis and numerical example.
FUZZY SETS AND SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Manman Yuan et al.
Summary: This article addresses the exponential synchronization issue of memristor-based complex-valued neural networks with time-varying uncertainties by feedback control. The proposed algorithm not only ensures the stability of the system, but also converts the sensitivity measure of encryption and decryption into synchronization error, suitable for image protection. Simulation examples are provided to verify the efficacy of the proposed synchronization criterion and its practical application on image protection.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Mathematics, Applied
R. Vadivel et al.
Summary: This paper investigates the bifurcation, stability, and stabilization analysis of PMSM systems, suggesting new delay-dependent sufficient conditions and sampled data control methods to ensure system stability. The efficacy of the techniques established in this paper is demonstrated in verification examples.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2021)
Article
Automation & Control Systems
Chaouki Aouiti et al.
Summary: This study proposes a method to achieve finite-time and fixed-time synchronization of delayed complex-valued recurrent neural networks with discontinuous activation functions and nonidentical parameters through sliding mode control. By constructing Lyapunov functionals and using the differential inequality technique, sufficient conditions are derived to guarantee synchronization. The effectiveness of the proposed methods is illustrated through two simulation examples.
EUROPEAN JOURNAL OF CONTROL
(2021)
Article
Automation & Control Systems
Huaicheng Yan et al.
Summary: This paper investigates the sliding mode control problem for a class of continuous-time switched neural networks with MDADT, and proposes a novel sliding mode controller based on an event-triggered mechanism. The sufficient conditions for stochastically exponentially stable closed-loop system are derived.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Xiaona Song et al.
Summary: This paper explores a novel class of nonlinear interconnected neural networks in the complex domain, obtaining a finite/fixed-time synchronization criterion for N subsystems with the design of a suitable nonlinear controller. The criteria for synchronization in finite time and fixed time are integrated into a unified theorem, and a secret communication example is presented to verify the validity and practicability of the research.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Interdisciplinary Applications
R. Vadivel et al.
Summary: This study investigates the finite-time event-triggered approach for recurrent neural networks with a leakage term and its application. By utilizing novel inequality techniques and the Lyapunov-Krasovskii functional method, the finite-time stability analysis of the system is ensured.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2021)
Article
Automation & Control Systems
R. Vadivel et al.
Summary: This article presents a dynamic model of PMSM based on Takagi-Sugeno fuzzy model and a reliable H-infinity control method to enhance the performance of PMSM. By taking into account load torque variation and stochastic actuator faults, the robust asymptotic stability of the closed-loop PMSM is ensured.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Mathematics, Interdisciplinary Applications
R. Vadivel et al.
Summary: This article investigates strict dissipativity synchronization for a class of static neural networks under an event-triggered scheme, proposing a design scheme and sufficient conditions based on LMIs, and demonstrating the performance of the derived results through simulation examples.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Mechanical
Runan Guo et al.
Summary: This paper investigates the problem of fixed-time synchronization for delayed complex-valued neural networks with inertial term, proposing two different controllers that can achieve perfect synchronization in a fixed time for networks with different types of activation functions. Synchronization criteria in terms of matrix inequalities and estimates of the settling times are derived, utilizing innovative inequalities in the complex field, representing an advancement of existing research progress. Numerical simulations for various types of activation functions are provided to support the theoretical results.
NONLINEAR DYNAMICS
(2021)
Article
Computer Science, Artificial Intelligence
Haibo Bao et al.
Summary: This article focuses on adaptive synchronization for a class of fractional-order coupled neural networks with output coupling. Novel adaptive output controllers with logarithm quantization are designed, and sufficient conditions for synchronization are built based on fractional-order Lyapunov functionals and LMIs. Numerical simulation results substantiate the applicability of the proposed approach.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Automation & Control Systems
Liang Feng et al.
Summary: This article addresses the synchronization issue in finite and fixed time for fully complex-variable delayed neural networks with discontinuous activations and time-varying delays. By introducing a complex-valued sign function and developing two discontinuous control strategies, synchronization criteria and estimates of settling time are derived using nonsmooth analysis and novel inequality techniques in the complex field. The unified control strategy designed under a new norm framework reveals that a parameter value in the controller determines whether the networks synchronize in finite or fixed time, supported by numerical results for an example provided in the article.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Automation & Control Systems
Xiaona Song et al.
Summary: This article proposes a novel generalized neural network model with Markovian jump parameters, inertial items, and reaction-diffusion terms, and discusses the issue of finite-time dissipative synchronization. By employing variable substitution and designing a novel time-varying memory-based controller, the synchronization of drive and response systems with less conservative criteria is ensured. The feasibility, superiority, and practicality of the results are illustrated through three examples.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Multidisciplinary
Ze Tang et al.
Summary: This paper investigates the exponential synchronization problem on a class of coupled heterogeneous neural networks with hybrid time-varying delays by introducing a distributed pinning control strategy. Sufficient conditions for achieving exponential quasi-synchronization are obtained by applying the concept of average impulsive intervals, the extended comparison principle of impulsive systems, and vector norm techniques. Two different situations of exponential synchronization are considered based on the different roles of impulsive effects in network synchronizing.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Multidisciplinary
Ruoyu Wei et al.
Summary: This paper introduces the novel concepts of fixed-time output synchronization and fixed-time H-infinity output synchronization, extending the results to coupled reaction-diffusion neural networks. By taking into consideration output delayed coupling and discontinuous activations, a novel feedback control scheme is proposed to ensure fixed-time output synchronization and H-infinity output synchronization of the considered CRDNNs. Numerical examples are provided to validate the correctness of the proposed results.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2021)
Article
Computer Science, Information Systems
R. Anbuvithya et al.
Summary: This paper discusses the extended dissipativity and non-fragile synchronization of delayed recurrent neural networks (RNNs) with multiple time-varying delays and sampled-data control. A suitable Lyapunov-Krasovskii Functional (LKF) is used to prove the stability condition of delayed RNNs, and a non-fragile sampled-data approach is applied to investigate the synchronization problem. The effectiveness of the suggested approach is confirmed through numerical simulations and comparative results.
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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2020)
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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2020)
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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2019)
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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2016)
Article
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Xinsong Yang et al.
COMMUNICATIONS IN NONLINEAR SCIENCE AND NUMERICAL SIMULATION
(2014)
Article
Computer Science, Interdisciplinary Applications
QX Xie et al.
MATHEMATICAL AND COMPUTER MODELLING
(2002)
