Robust Exponential Synchronization for Stochastic Delayed Neural Networks with Reaction–Diffusion Terms and Markovian Jumping Parameters
Sign Up to like & getrecommendations! Published in 2017 at "Neural Processing Letters"
DOI: 10.1007/s11063-017-9756-6
Abstract: This paper investigates robust exponential synchronization for stochastic delayed neural networks with reaction–diffusion terms and Markovian jumping parameters driven by infinite dimensional Wiener processes. The novelty of this paper lives in the use of a… read more here.
Keywords: synchronization stochastic; stochastic delayed; robust exponential; synchronization ... See more keywords
Dynamics of delayed neural field models in two-dimensional spatial domains
Sign Up to like & getrecommendations! Published in 2022 at "Journal of Differential Equations"
DOI: 10.1016/j.jde.2022.02.002
Abstract: Delayed neural field models can be viewed as a dynamical system in an appropriate functional analytic setting. On two dimensional rectangular space domains, and for a special class of connectivity and delay functions, we describe… read more here.
Keywords: neural field; field models; equation; delayed neural ... See more keywords
Synchronization of memristive delayed neural networks via hybrid impulsive control
Sign Up to like & getrecommendations! Published in 2017 at "Neurocomputing"
DOI: 10.1016/j.neucom.2017.06.028
Abstract: Abstract Synchronization control problem is an important problem for the dynamical behaviors of neural networks. In this paper, by structuring hybrid impulsive and feedback controllers, synchronization problem of the memristive delayed neural networks is firstly… read more here.
Keywords: memristive delayed; hybrid impulsive; neural networks; control ... See more keywords
Novel results on dissipativity analysis for generalized delayed neural networks
Sign Up to like & getrecommendations! Published in 2019 at "Neurocomputing"
DOI: 10.1016/j.neucom.2018.12.013
Abstract: Abstract This study investigates the exponential stability and dissipativity issues for generalized neural networks with mixed time-varying delayed signals. The objective of the present work is to determine whether the new exponential stability and dissipativity… read more here.
Keywords: dissipativity; neural networks; analysis; generalized delayed ... See more keywords
Asymptotic Synchronization Control of Discrete-Time Delayed Neural Networks With a Reuse Mechanism Under Missing Data and Uncertainty
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DOI: 10.1109/access.2018.2870729
Abstract: This paper focuses on the mean-square asymptotic synchronization of discrete-time delayed neural networks with missing data and uncertainty. The unreliable communication links between neural networks are considered, and the process of missing data is modeled… read more here.
Keywords: discrete time; neural networks; time delayed; asymptotic synchronization ... See more keywords
Passivity Analysis of Delayed Neural Networks Based on Lyapunov–Krasovskii Functionals With Delay-Dependent Matrices
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Transactions on Cybernetics"
DOI: 10.1109/tcyb.2018.2874273
Abstract: This paper is concerned with passivity of a class of delayed neural networks. In order to derive less conservative passivity criteria, two Lyapunov–Krasovskii functionals (LKFs) with delay-dependent matrices are introduced by taking into consideration a… read more here.
Keywords: passivity; delayed neural; neural networks; dependent matrices ... See more keywords
Event-Triggered Output-Feedback Control for Synchronization of Delayed Neural Networks.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on cybernetics"
DOI: 10.1109/tcyb.2022.3163378
Abstract: This article proposes a novel discrete event-triggered scheme (DETS) for the synchronization of delayed neural networks (NNs) using the dynamic output-feedback controller (DOFC). The proposed DETS uses both the current and past samples to determine… read more here.
Keywords: event triggered; neural networks; synchronization delayed; event ... See more keywords
Novel Heterogeneous Mode-Dependent Impulsive Synchronization for Piecewise T-S Fuzzy Probabilistic Coupled Delayed Neural Networks
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Fuzzy Systems"
DOI: 10.1109/tfuzz.2021.3076525
Abstract: This article investigates the heterogeneous impulsive synchronization for T-S fuzzy probabilistic coupled delayed neural networks (CDNNs) with mode-dependent parameters and piecewise membership functions. To begin with, a novel CDNNs model with adjustable coupling strength and… read more here.
Keywords: fuzzy probabilistic; delayed neural; impulsive synchronization; mode dependent ... See more keywords
Improved Stability Analysis for Delayed Neural Networks
Sign Up to like & getrecommendations! Published in 2018 at "IEEE Transactions on Neural Networks and Learning Systems"
DOI: 10.1109/tnnls.2017.2743262
Abstract: In this brief, by constructing an augmented Lyapunov–Krasovskii functional in a triple integral form, the stability analysis of delayed neural networks is investigated. In order to exploit more accurate bounds for the derivatives of triple… read more here.
Keywords: stability analysis; delayed neural; neural networks; analysis delayed ... See more keywords
Type-Dependent Average Dwell Time Method and Its Application to Delayed Neural Networks With Large Delays.
Sign Up to like & getrecommendations! Published in 2022 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2022.3184712
Abstract: This article investigates the stability of delayed neural networks with large delays. Unlike previous studies, the original large delay is separated into several parts. Then, the delayed neural network is viewed as the switched system… read more here.
Keywords: neural networks; delayed neural; large delays; type dependent ... See more keywords
Stability and Bifurcation Exploration of Delayed Neural Networks With Radial-Ring Configuration and Bidirectional Coupling.
Sign Up to like & getrecommendations! Published in 2023 at "IEEE transactions on neural networks and learning systems"
DOI: 10.1109/tnnls.2023.3240403
Abstract: For decades, studying the dynamic performances of artificial neural networks (ANNs) is widely considered to be a good way to gain a deeper insight into actual neural networks. However, most models of ANNs are focused… read more here.
Keywords: bifurcation; ring configuration; neural networks; delayed neural ... See more keywords