A stochastic version of the Jansen and Rit neural mass model: analysis, numerics and filtering

Keyphrases

• Numerics 100%
• Stochastic Version 100%
• Neural Mass Model 100%
• Model Filtering 100%
• Filter Method 40%
• Continuous-time 40%
• Particle Filter 40%
• Nonlinear Filtering 40%
• Inverse Problem 20%
• Parameter Setting 20%
• Qualitative Behavior 20%
• Neural Dynamics 20%
• Path Properties 20%
• Stochastic Hamiltonian Systems 20%
• Stability Results 20%
• Invariant Measure 20%
• Mesoscopic 20%
• Long-term Stability 20%
• Random Inputs 20%
• Asymptotic Behavior 20%
• Geometric Ergodicity 20%
• Nonlinear Displacement 20%
• Splitting Approach 20%
• Efficient numerical Scheme 20%
• Better Approximation 20%
• Structure Preservation 20%
• Specific Parameters 20%
• Euler-Maruyama Scheme 20%
• Numerical Splitting 20%
• Filtering Framework 20%
• Time Discretization Scheme 20%
• Given Accuracy 20%
• Discretization Step 20%
• Numerical Approximation 20%
• Stochastic Ordinary Differential Equations 20%
• Splitting Scheme 20%
• Splitting Integrators 20%

Mathematics

• Numerics 100%
• Stochastics 100%
• Continuous Time 28%
• Approximates 28%
• Discretization 14%
• Numerical Scheme 14%
• Qualitative Behavior 14%
• Random Input 14%
• Ergodicity 14%
• Stability Result 14%
• Hamiltonian Systems 14%
• Asymptotic Behavior 14%
• Invariant Measure 14%
• Neural Dynamic 14%
• Concludes 14%
• Ordinary Differential Equation 14%
• Numerical Approximation 14%
• Initial Value 14%
• Time Discretization 14%