Stability of delayed inertial neural networks on time scales: a unified matrix-measure approach
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Publication:2057695
DOI10.1016/j.neunet.2020.06.020zbMath1478.93564OpenAlexW3037620381WikidataQ96770387 ScholiaQ96770387MaRDI QIDQ2057695
Publication date: 7 December 2021
Published in: Neural Networks (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.neunet.2020.06.020
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Existence and global asymptotic stability criteria for nonlinear neutral-type neural networks involving multiple time delays using a quadratic-integral Lyapunov functional ⋮ Global \(\mu \)-stabilization of quaternion-valued inertial BAM neural networks with time-varying delays via time-delayed impulsive control ⋮ Passivity-based synchronization for Markov switched neural networks with time delays and the inertial term ⋮ An inertial neural network approach for loco-manipulation trajectory tracking of mobile robot with redundant manipulator ⋮ Globally asymptotic stability analysis for memristor‐based competitive systems of reaction–diffusion delayed neural networks ⋮ Stability analysis based on a control adjuster for switched neural networks by trajectory similarity ⋮ Cluster synchronization for directed coupled inertial reaction-diffusion neural networks with nonidentical nodes via non-reduced order method ⋮ Novel criteria for robust stability of Cohen-Grossberg neural networks with multiple time delays ⋮ Global exponential stability of almost periodic solutions for quaternion-valued RNNs with mixed delays on time scales
Cites Work
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- Fixed-time synchronization of inertial memristor-based neural networks with discrete delay
- Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays
- Exponential stability for a class of memristive neural networks with mixed time-varying delays
- An estimation of the domain of attraction and convergence rate for Hopfield continuous feedback neural networks
- Global exponential stabilization of impulsive neural networks with unbounded continuously distributed delays
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