Pages that link to "Item:Q2251515"
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The following pages link to Laws of large numbers and Langevin approximations for stochastic neural field equations (Q2251515):
Displaying 15 items.
- Spatio-temporal averaging for a class of hybrid systems and application to conductance-based neuron models (Q313354) (← links)
- Finite-size effects on traveling wave solutions to neural field equations (Q723664) (← links)
- Numerical solution of the neural field equation in the presence of random disturbance (Q2223831) (← links)
- Large deviations for nonlocal stochastic neural fields (Q2251604) (← links)
- A gradient flow formulation for the stochastic Amari neural field model (Q2330609) (← links)
- Spatio-temporal hybrid (PDMP) models: central limit theorem and Langevin approximation for global fluctuations. Application to electrophysiology (Q2348722) (← links)
- Stochastic neural field equations: a rigorous footing (Q2355787) (← links)
- Large deviations for estimators of the parameters of a neuronal response latency model (Q2405922) (← links)
- Accuracy analysis of numerical simulations and noisy data assimilations in two-dimensional stochastic neural fields with infinite signal transmission speed (Q2680261) (← links)
- A multiscale analysis of traveling waves in stochastic neural fields (Q2819092) (← links)
- Fluid limit theorems for stochastic hybrid systems with application to neuron models (Q3059695) (← links)
- Random fields and probability distributions with given marginals on randomly correlated systems: a general method and a problem from theoretical neuroscience (Q4495881) (← links)
- Mean field dynamics of a Wilson–Cowan neuronal network with nonlinear coupling term (Q4561042) (← links)
- Global computation of phase-amplitude reduction for limit-cycle dynamics (Q4683666) (← links)
- Fast optimal entrainment of limit-cycle oscillators by strong periodic inputs via phase-amplitude reduction and Floquet theory (Q6556969) (← links)
