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Article
Computer Science, Interdisciplinary Applications
Qiu Peng et al.
Summary: This paper investigates the global Mittag-Leffler synchronization of fractional-order inertial-type neural networks with time delays. Two control schemes, namely state feedback control and fractional-order adaptive control, are proposed. By using variable substitution, the original fractional-order inertial system is transformed into a traditional fractional-order system. The results are established based on Lyapunov stability theory and fractional-order differential inequalities. Numerical examples are provided to validate the effectiveness of the obtained results.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2023)
Article
Automation & Control Systems
Lian Duan et al.
Summary: This paper presents theoretical results on finite-time synchronization of two delayed inertial fuzzy neural networks, utilizing adjustable parameters and a general Lyapunov function. The analysis mainly employs finite-time stability theory, Lyapunov functional method, and inequality techniques, and numerical simulations are conducted to demonstrate the effectiveness of the theoretical results.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Zhiying Li et al.
Summary: This paper investigates the boundedness and global Mittag-Leffler synchronization of fractional-order inertial Cohen-Grossberg neural networks with time delays. By utilizing the properties of Riemann-Liouville fractional-order calculus, proper variable substitutions, and the differential mean-value theorem, sufficient conditions for the boundedness and synchronization are derived. Two numerical examples are simulated to validate the theorems.
NEURAL PROCESSING LETTERS
(2022)
Article
Mathematics, Applied
Chaouki Aouiti et al.
Summary: This paper investigates the finite-time stabilization of fractional-order inertial neural networks (FOINNs). By employing variable substitution and establishing Lyapunov functionalities, as well as using new control algorithms, novel criteria for achieving finite-time stabilization of the system are proposed. Two examples are provided to demonstrate the effectiveness and feasibility of the obtained results.
NONLINEAR ANALYSIS-MODELLING AND CONTROL
(2022)
Article
Automation & Control Systems
Peng Wan et al.
Summary: This article proposes a Takagi-Sugeno fuzzy second-fractional-order linear network and provides a sufficient criterion for ensuring global asymptotic stability of the network. It also designs a fuzzy state-feedback control scheme and an adaptive control method. Simulation results demonstrate the effectiveness of the theoretical results.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Mathematics, Applied
Yuhong Cheng et al.
Summary: This paper focuses on the global Mittag-Leffler synchronization for fractional-order inertial neural networks with Caputo derivative and delay. By using variable transformation, delayed-feedback controller, fractional Lyapunov functional approach, and inequality analysis technique, novel algebraic criteria on the global M-L synchronization are established. The proposed results are characterized by algebraic inequalities form, which simplifies calculation and facilitates testing. Two numerical examples validate the theoretical results.
JOURNAL OF APPLIED MATHEMATICS AND COMPUTING
(2022)
Article
Mathematics, Applied
Huizhen Qu et al.
Summary: This paper investigates the global dynamics in fractional-order dual inertial neural networks with time lags, studying the asymptotic stability and S-asymptotically omega-periodic oscillation of the model. The feasibility and effectiveness of the obtained conclusions are supported by numerical examples. This research fills some gaps in the field.
Article
Automation & Control Systems
Tingting Zhang et al.
Summary: This article studies the global exponential synchronization of quaternion-valued memristive delayed neural networks using quantized intermittent control. By introducing two quantized intermittent control strategies and applying Lyapunov functional method and inequality techniques, new delay-dependent criteria in the form of real-valued algebraic inequalities are derived to ensure the synchronization of the system. Compared to traditional feedback control, quantized intermittent control reduces control expenses and achieves synchronization in a shorter time.
Article
Computer Science, Artificial Intelligence
Peng Wan et al.
Summary: This article introduces a new approach to judge the Lagrange stability of neural networks with distributed time delays by introducing scale-limited Halanay inequality and time scale theory. The proposed method is verified to be effective through numerical simulations.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Mathematics, Interdisciplinary Applications
Fei Wang et al.
Summary: This paper investigates the quasi-synchronization problem of a heterogeneous dynamical network with fractional order dynamical behavior and time-varying delay. It applies the distributed impulsive control strategy and discusses both synchronizing impulses and desynchronizing impulses.
CHAOS SOLITONS & FRACTALS
(2021)
Article
Engineering, Mechanical
A. G. Cunha-Filho et al.
Summary: This paper discusses the application of fractional calculus combined with the finite element method in modeling viscoelastic systems, proposing a new and efficient three-dimensional fractional constitutive formulation based on a recurrence term to describe the behavior of viscoelastic materials, especially for complex systems. The efficiency and accuracy of this proposed formulation are demonstrated through an academic example compared to existing methods.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Xueqi Yao et al.
Summary: This study addresses the stability and synchronization problems for the memristor-based fractional-order fuzzy cellular neural networks with multiple delays. Three exponential stability criteria are derived using Laplace transform method, fractional-order calculus approach, and the method of complex function. Compared with existing results, novel exponentially stable and synchronization conditions have been proposed. The obtained results are applicable to both fractional-order systems and integer-order systems, and their validity and merits are illustrated through examples.
Article
Computer Science, Artificial Intelligence
Mengying Yan et al.
Summary: This paper investigates the passivity of uncertain BAM inertial neural networks with time-varying delays, proposing new Lyapunov functionals and delay-dependent criteria based on linear matrix inequalities to ensure the passivity of the systems. Numerical simulations demonstrate the effectiveness of the proposed approach.
Article
Computer Science, Artificial Intelligence
Fanchao Kong et al.
Summary: This article focuses on the fixed-time synchronization of discontinuous fuzzy inertial neural networks with time-varying delays, using new improved fixed-time stability lemmas. By establishing error systems and proving new stability lemmas, the setting times are estimated more accurately compared to previous methods. A numerical example is conducted to verify the correctness and advantages of the main results.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Jigui Jian et al.
Summary: This article focuses on the global Mittag-Leffler boundedness for fractional-order fuzzy quaternion-valued neural networks, by separating the system and deriving effective conditions through inequalities to ensure global boundedness, and presenting the framework of global Mittag-Leffler attracting sets.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Tingting Zhang et al.
Summary: This article studies the global asymptotic synchronization of second-order fuzzy memristive neural networks with infinite distributed and time-varying delays through feedback control and adaptive control schemes. New criteria are directly acquired based on Lyapunov stability theory and Barbalat Lemma to ensure the synchronization. The global asymptotic synchronization is directly analyzed via new Lyapunov-Krasovskii functionals without reduced-order means, compared to existing methods.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Liang Ke
Summary: This paper investigates the stability of a class of fractional-order inertial neural networks with time-delay, obtaining sufficient conditions for Mittag-Leffler stability and asymptotical omega-periodicity through appropriate transformations. The theoretical results are verified by numerical simulations.
Article
Automation & Control Systems
Yin Sheng et al.
Summary: This article investigates the global exponential stabilization of inertial memristive neural networks with discrete and distributed time-varying delays, presenting the stability in terms of algebraic inequalities. The study also extends existing results and examines the impact of inertial terms and variable transformations on the stability of DIMNNs.
IEEE TRANSACTIONS ON CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Kai Wu et al.
Summary: This article focuses on the global robust exponential dissipativity (GRED) of uncertain second-order BAM neural networks with mixed time-varying delays. New differential inequalities and Lyapunov-Krasovskii functionals are established to present new GRED criteria in the form of linear matrix inequalities. The correctness of the theoretical results is verified through simulation experiments.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Shuailei Zhang et al.
Summary: This paper investigates the synchronization of a Riemann-Liouville-type fractional inertial neural network with a time delay and two inertial terms. New Lyapunov functions are constructed and two new synchronization criteria are provided based on linear matrix inequalities (LMIs). Suitable controllers are designed to ensure synchronization between the master and slave systems, and numerical examples demonstrate the effectiveness and superiority of the criteria.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Computer Science, Artificial Intelligence
Zhenjie Wang et al.
Summary: This paper investigates the finite-time synchronization problem of fuzzy inertial cellular neural networks with time-varying delays. By constructing suitable Lyapunov functional and utilizing integral inequality techniques, the proposed method is relatively convenient to solve the problem, extending the research works on the finite-time synchronization of these networks. Numerical simulations verify the effectiveness of the proposed results.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(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
Computer Science, Theory & Methods
Jigui Jian et al.
FUZZY SETS AND SYSTEMS
(2020)
Article
Mathematics, Interdisciplinary Applications
Qi Wang et al.
CHAOS SOLITONS & FRACTALS
(2020)
Article
Automation & Control Systems
Shuai Yang et al.
IEEE TRANSACTIONS ON CYBERNETICS
(2020)
Article
Computer Science, Artificial Intelligence
Renyu Ye et al.
NEURAL PROCESSING LETTERS
(2019)
Article
Computer Science, Artificial Intelligence
Yajuan Gu et al.
Article
Computer Science, Artificial Intelligence
Hong-Li Li et al.
Article
Mathematics, Interdisciplinary Applications
Li Wang et al.
CHAOS SOLITONS & FRACTALS
(2019)
Article
Computer Science, Artificial Intelligence
Shuai Yang et al.
Article
Automation & Control Systems
Jiyang Chen et al.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2018)
Article
Computer Science, Artificial Intelligence
Xuanying Li et al.
Article
Computer Science, Artificial Intelligence
Peng Wan et al.
Article
Computer Science, Artificial Intelligence
Shiping Wen et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2017)
Correction
Computer Science, Artificial Intelligence
Juan Yu et al.
Article
Computer Science, Artificial Intelligence
Fei Wang et al.
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Hu Wang et al.
Article
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Chao Song et al.
