Stability analysis of fractional reaction-diffusion memristor-based neural networks with neutral delays via Lyapunov functions

Wu, Xiang; Liu, Shutang; Wang, Huiyu; Sun, Jie; Wang, Qiao

doi:10.1016/j.neucom.2023.126497

Cited by 4 publications

(2 citation statements)

References 40 publications

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“…The cluster synchronization for neutral stochastic delay networks at exponential rates with time-varying delays is addressed in [21] via a periodically intermittent pinning adaptive control strategy. Stability analysis of fractional reaction-diffusion memristorbased neural networks with neutral delays via Lyapunov functions is discussed in [22] by designing a state feedback controller. The adaptive synchronization problem for a class of neutral coupled neural networks with mixed delays is studied in [23], which includes distributed delays, state delays, coupling delays and exponential synchronization problem of neutral neural network with Lévy noise is investigated in [24].…”

Section: Introductionmentioning

confidence: 99%

Event-Triggered Synchronization Control of Uncertain Neutral-Type Neural Networks With Time-Varying Delays and Actuator Saturation

Duan,

Tian

2024

IEEE Access

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A class of event-triggered synchronization control of uncertain neutral-type neural networks (NTNNs) with time-varying delays and actuator saturation is discussed in this paper. We propose a novel NTNNs model by combining it with an event-triggered mechanism (ETM), actuator saturation and uncertainty. The ETM is introduced to determine whether the sampled signals should be transmitted to controller or not and actuator saturation is considered due to the complex network environment in reality. With the aid of proper Lyapunov-Krasovskii functional (LKF), some sufficient conditions for asymptotic stability of synchronization error system are derived and the gain of the controller is obtained by using linear matrix inequality (LMI) and free-weight matrix (FWM) methods. Finally, we use Euler-Maruyama numerical mechanism to simulate the drive-response systems and the error system, which shows the good convergence performance of our synchronization model. Two numerical examples in the end of this paper demonstrate the effectiveness of the proposed method.INDEX TERMS synchronization, neutral-type neural networks (NTNNs), event-triggered mechanism (ETM), actuator saturation, free-weight matrix (FWM).

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Section: Introductionmentioning

confidence: 99%

Event-Triggered Synchronization Control of Uncertain Neutral-Type Neural Networks With Time-Varying Delays and Actuator Saturation

Duan,

Tian

2024

IEEE Access

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“…It is natural that this type of delay was also added to neural network models, because they have been seen to appear when VLSI circuits are used for implementing neural networks. FONNs with neutral-type delays were the focus of the following recent papers: [20,21,26,[57][58][59].…”

Section: Introductionmentioning

confidence: 99%

Asymptotic and Mittag–Leffler Synchronization of Fractional-Order Octonion-Valued Neural Networks with Neutral-Type and Mixed Delays

Popa

2023

Fractal Fract

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Very recently, a different generalization of real-valued neural networks (RVNNs) to multidimensional domains beside the complex-valued neural networks (CVNNs), quaternion-valued neural networks (QVNNs), and Clifford-valued neural networks (ClVNNs) has appeared, namely octonion-valued neural networks (OVNNs), which are not a subset of ClVNNs. They are defined on the octonion algebra, which is an 8D algebra over the reals, and is also the only other normed division algebra that can be defined over the reals beside the complex and quaternion algebras. On the other hand, fractional-order neural networks (FONNs) have also been very intensively researched in the recent past. Thus, the present work combines FONNs and OVNNs and puts forward a fractional-order octonion-valued neural network (FOOVNN) with neutral-type, time-varying, and distributed delays, a very general model not yet discussed in the literature, to our awareness. Sufficient criteria expressed as linear matrix inequalities (LMIs) and algebraic inequalities are deduced, which ensure the asymptotic and Mittag–Leffler synchronization properties of the proposed model by decomposing the OVNN system of equations into a real-valued one, in order to avoid the non-associativity problem of the octonion algebra. To accomplish synchronization, we use two different state feedback controllers, two different types of Lyapunov-like functionals in conjunction with two Halanay-type lemmas for FONNs, the free-weighting matrix method, a classical lemma, and Young’s inequality. The four theorems presented in the paper are each illustrated by a numerical example.

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Pointwise-Measurement-Based Event-Triggered Synchronization of Reaction-Diffusion Neural Networks

Zheng,

Song

2023

Communications in Computer and Information Science

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Stability analysis of fractional reaction-diffusion memristor-based neural networks with neutral delays via Lyapunov functions

Cited by 4 publications

References 40 publications

Event-Triggered Synchronization Control of Uncertain Neutral-Type Neural Networks With Time-Varying Delays and Actuator Saturation

Event-Triggered Synchronization Control of Uncertain Neutral-Type Neural Networks With Time-Varying Delays and Actuator Saturation

Asymptotic and Mittag–Leffler Synchronization of Fractional-Order Octonion-Valued Neural Networks with Neutral-Type and Mixed Delays

Pointwise-Measurement-Based Event-Triggered Synchronization of Reaction-Diffusion Neural Networks

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