The split-step \(\theta \)-methods for stochastic delay Hopfield neural networks
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Publication:693457
DOI10.1016/j.apm.2011.10.020zbMath1252.65122OpenAlexW2042190725MaRDI QIDQ693457
Publication date: 7 December 2012
Published in: Applied Mathematical Modelling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.apm.2011.10.020
numerical solutionsmean-square stabilitysplit-step \(\theta \)-methodsstochastic delay Hopfield neural networks
Related Items (10)
Improving split-step forward methods by ODE solver for stiff stochastic differential equations ⋮ Mean square stability of two classes of theta methods for numerical computation and simulation of delayed stochastic Hopfield neural networks ⋮ Convergence and stability of the split-step \(\theta\)-Milstein method for stochastic delay Hopfield neural networks ⋮ Mean square exponential stability of stochastic Hopfield neural networks with mixed delays ⋮ Global exponential convergence of neutral-type Hopfield neural networks with multi-proportional delays and leakage delays ⋮ The balanced split step theta approximations of stochastic neutral Hopfield neural networks with time delay and Poisson jumps ⋮ Strong convergence of the split-step \(\theta\)-method for stochastic age-dependent capital system with Poisson jumps and fractional Brownian motion ⋮ Mean square stability and almost sure exponential stability of two step Maruyama methods of stochastic delay Hopfield neural networks ⋮ Exponential stability and numerical methods of stochastic recurrent neural networks with delays ⋮ Strong convergence and almost sure exponential stability of balanced numerical approximations to stochastic delay Hopfield neural networks
Cites Work
- Convergence and stability of the split-step \(\theta \)-method for stochastic differential equations
- Stability of the split-step backward Euler scheme for stochastic delay integro-differential equations with Markovian switching
- Split-step forward methods for stochastic differential equations
- Exponential stability of stochastic delayed Hopfield neural networks
- Mean square exponential stability of stochastic delayed Hopfield neural networks
- Exponential stability of numerical solutions to stochastic delay Hopfield neural networks
- Convergence and stability of the split-step backward Euler method for linear stochastic delay integro-differential equations
- Almost sure exponential stability of neutral stochastic differential difference equations
- Strong Convergence of Euler-Type Methods for Nonlinear Stochastic Differential Equations
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