This paper focuses on Lagrange exponential stability and finite-time stabilization of Takagi-Sugeno (T-S) fuzzy memristive neural networks with discrete distributed time-varying delays (DFMNNs). By resorting to theories differential inclusions the comparison strategy, an algebraic condition is developed confirm underlying DFMNNs in Filippov's sense, exponentially attractive set estimated. When external input not considered, global derived directly, which includes some existing ones as...

This paper is concerned with synchronization for a class of reaction-diffusion neural networks Dirichlet boundary conditions and infinite discrete time-varying delays. By utilizing theories partial differential equations, Green's formula, inequality techniques, the concept comparison, algebraic criteria are presented to guarantee master-slave underlying via designed controller. Additionally, sufficient on exponential finite delays established. The proposed herein enhance generalize some...

In this article, exponential synchronization of complex dynamical networks (CDNs) on time scales is researched. An IDET control strategy designed to decrease the number event-triggered updating instants. Leveraging intermittent event detections and sampling, combining analytical method with time-scale theory, criteria are obtained for underlying CDNs. Moreover, a parameter selection algorithm given acquire parameters. addition, two lemmas functions proposed prove exclusion Zeno behavior. Two...

This paper is concerned with exponential stabilization for a class of Takagi-Sugeno fuzzy memristive neural networks (FMNNs) unbounded discrete and distributed time-varying delays. Under the framework Filippov solutions, algebraic criteria are established to guarantee addressed FMNNs hybrid time delays via designing state feedback controller by exploiting inequality techniques, calculus theorems, theories sets. The obtained results in this enhance generalize some existing ones. Meanwhile,...

This paper investigates the synchronization issue of coupled reaction-diffusion neural networks with directed topology via an adaptive approach. Due to complexity network structure and presence space variables, it is difficult design proper strategies on coupling weights accomplish synchronous goal. Under assumptions two kinds special structures, that is, spanning path tree, some novel edge-based laws, which utilized local information node dynamics fully are designed for reaching...

In this paper, stabilization for a class of Takagi-Sugeno (T-S) fuzzy memristive neural networks (FMNNs) with mixed time delays is investigated. By virtue theories differential equations discontinuous right-hand sides, inequality techniques, and the comparison method, an algebraic criterion derived to stabilize addressed FMNNs bounded discrete distributed via designed state feedback controller in Filippov's sense. The result can be reinforced unbounded delays. Meanwhile, exponential...

This article investigates the global exponential stabilization (GES) of inertial memristive neural networks with discrete and distributed time-varying delays (DIMNNs). By introducing term into (MNNs), DIMNNs are formulated as second-order differential equations discontinuous right-hand sides. Via a variable transformation, initial rewritten first-order equations. exploiting theories inclusion, inequality techniques, comparison strategy, pth moment GES (p ≥ 1) addressed is presented in terms...

This paper investigates the φ-type stability and robust for a general class of stochastic reaction-diffusion neural networks (SRDNNs) with Dirichlet boundary conditions, infinite discrete time-varying delays, continuously distributed delays. By virtue inequality techniques, properties M-matrix, theories analysis, several sufficient criteria are obtained to guarantee almost sure stability, pth moment underlying SRDNNs hybrid unbounded time With appropriate choices function φ, reduces...

This article investigates global exponential stabilization (GES) of Takagi–Sugeno (T–S) fuzzy memristive neural networks with multiple time-varying delays (DFMNNs) via intermittent control strategy. By resorting to differential inclusion theory, comparison means, and inequality techniques, some results are developed ensure GES the underlying DFMNNs a state feedback law within sense Filippov. The outcome is generalized FMNNs infinite distributed time delays. Additionally, stability discrete...

This paper considers the tracking synchronization problem for a class of coupled reaction-diffusion neural networks (CRDNNs) with undirected topology. For case where trajectory has identical individual dynamic as that network nodes, edge-based and vertex-based adaptive strategies on coupling strengths well controllers, which demand merely local neighbor information, are proposed to synchronize CRDNNs trajectory. To reduce control costs, an pinning technique is employed. different from...

This article focuses on the finite-time stabilization problem for fuzzy spatiotemporal competitive neural networks (FSCNNs) with discrete and distributed delays. First, differentiable conditions finite delays in FSCNNs are removed, constraints of kernel function infinite weakened. Then, a novel partial differential inequality is proposed to handle spatial diffusions, which relaxes restriction symmetric around origin bounded domain. To stabilize within time, control strategy without...

This paper deals with the global exponential stability for delayed recurrent neural networks (DRNNs). By constructing an augmented Lyapunov-Krasovskii functional and adopting reciprocally convex combination approach Wirtinger-based integral inequality, delay-dependent criteria are derived in terms of linear matrix inequalities. Meanwhile, a general effective method on analysis DRNNs is given through lemma, where convergence rate can be estimated. With this some asymptotic acquired previous...

This paper discusses finite-time synchronization of complex-valued neural networks (CVNNs) with infinite delays. By utilizing non-separation approach, analytical strategy, and inequality techniques, a criterion is constructed to ensure that CVNNs can be achieved. The designed controller only consists state feedback term sign function term. Finally, confirm the effectiveness theoretical outcomes, two numerical examples are given.

This paper investigates the stability and stabilization of Takagi-Sugeno (T-S) fuzzy systems with discrete distributed time-varying delays. First, pth moment global exponential (p≥1) addressed delayed is considered by virtue comparison approach inequality techniques. The developed algebraic criteria include some existing outcomes as special cases. Second, underlying performed under a state feedback controller. Third, considering that only few studies have been concerned finite-time T-S...

This article investigates finite-time stabilization of competitive neural networks with discrete time-varying delays (DCNNs). By virtue comparison strategies and inequality techniques, the underlying DCNNs is analyzed by designing a discontinuous state feedback controller, which simplifies controller design proof processes some existing results. Meanwhile, global exponential provided under continuous controller. In addition, stability shown as an M-matrix, contains published outcomes special...

This article is concerned with global exponential synchronization of delayed fuzzy neural networks reaction diffusions (RDFNNs). By adopting analytic method and some inequality techniques, a criterion in terms <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$p$</tex-math></inline-formula> -norm ( notation="LaTeX">$p\geq 2$</tex-math></inline-formula> ) obtained for the RDFNNs via adaptive intermittent...

This article investigates the Lagrange exponential stability and Lyapunov of memristive neural networks with discrete distributed time-varying delays (DMNNs). By means inequality techniques, theories M-matrix, comparison strategy, underlying DMNNs is considered in sense Filippov, globally exponentially attractive set estimated through employing M-matrix external input. Especially, when input not concerned, corresponding developed immediately form an which contains some published outcomes as...