Stability analysis of Hopfield neural networks with unbounded delay driven by G-Brownian motion
From MaRDI portal
Publication:5027388
DOI10.1080/00207179.2020.1775307zbMath1482.93511OpenAlexW3031358812MaRDI QIDQ5027388
Publication date: 4 February 2022
Published in: International Journal of Control (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207179.2020.1775307
G-Brownian motionunbounded time-varying delayG-mean square exponential stabilityG-mean square stability
Delay control/observation systems (93C43) Exponential stability (93D23) Networked control (93B70) Nonlinear processes (e.g., (G)-Brownian motion, (G)-Lévy processes) (60G65)
Related Items
Unnamed Item ⋮ Periodic dynamics for nonlocal Hopfield neural networks with random initial data ⋮ Almost sure exponential stability of nonlinear stochastic delay hybrid systems driven by \(G\)-Brownian motion
Cites Work
- Unnamed Item
- Exponential stability of solutions to impulsive stochastic differential equations driven by \(G\)-Brownian motion
- Lyapunov-type conditions and stochastic differential equations driven by \(G\)-Brownian motion
- Stopping times and related Itô's calculus with \(G\)-Brownian motion
- Stochastically asymptotic stability of delayed recurrent neural networks with both Markovian jump parameters and nonlinear disturbances
- Function spaces and capacity related to a sublinear expectation: application to \(G\)-Brownian motion paths
- Exponential stability for stochastic differential equation driven by G-Brownian motion
- Global stability analysis of impulsive Cohen-Grossberg neural networks with delay
- Stability for delayed reaction-diffusion neural networks
- Stability analysis of stochastic functional differential equations with infinite delay and its application to recurrent neural networks
- On representation theorem of \(G\)-expectations and paths of \(G\)-Brownian motion
- Long term behavior of a random Hopfield neural lattice model
- Stability of delayed Hopfield neural networks under a sublinear expectation framework
- Stability results for stochastic delayed recurrent neural networks with discrete and distributed delays
- Exponential stability of \(\theta\)-method for stochastic differential equations in the \(G\)-framework
- Mean-square stability of delayed stochastic neural networks with impulsive effects driven by \(G\)-Brownian motion
- Global asymptotic stability of stochastic complex-valued neural networks with probabilistic time-varying delays
- Periodic attractor for reaction-diffusion high-order Hopfield neural networks with time-varying delays
- Global exponential stability of nonautonomous neural network models with unbounded delays
- Stability equivalence between the stochastic differential delay equations driven by \(G\)-Brownian motion and the Euler-Maruyama method
- Existence and stability of solutions to highly nonlinear stochastic differential delay equations driven by \(G\)-Brownian motion
- Modeling and analysis of random and stochastic input flows in the chemostat model
- Asymptotical boundedness and stability for stochastic differential equations with delay driven by \(G\)-Brownian motion
- Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays
- Multi-dimensional \(G\)-Brownian motion and related stochastic calculus under \(G\)-expectation
- Global asymptotic stability of stochastic recurrent neural networks with multiple discrete delays and unbounded distributed delays
- Stochastic functional differential equations with infinite delay driven by G -Brownian motion
- Stability in Cohen–Grossberg-type bidirectional associative memory neural networks with time-varying delays
- Exponential stability and instability of stochastic neural networks1
- Sobolev-type stochastic differential equations driven by G-Brownian motion
- Quasi-sure exponential stability and stabilisation of stochastic delay differential equations under G-expectation framework
- Stationary oscillation of an impulsive delayed system and its application to chaotic neural networks
- Neural networks and physical systems with emergent collective computational abilities.
- Nonuniform behavior and stability of Hopfield neural networks with delay
- Stability analysis of impulsive stochastic Cohen–Grossberg neural networks driven by G-Brownian motion
- Stability of stochastic delay neural networks
- Hopfield neural networks for optimization: Study of the different dynamics