Pages that link to "Item:Q4655663"

The following pages link to NONLINEAR DYNAMICAL SYSTEM IDENTIFICATION FROM UNCERTAIN AND INDIRECT MEASUREMENTS (Q4655663):

Displaying 18 items.

• Observability and synchronization of neuron models (Q4644303) (← links)
• Parameter estimation of slow potassium dynamics in a neuron model for seizure-like activity via adaptive lag synchronization and unscented Kalman filter (Q4973151) (← links)
• Structure learning in coupled dynamical systems and dynamic causal modelling (Q4993457) (← links)
• Parameter Estimation in Multiple Dynamic Synaptic Coupling Model Using Bayesian Point Process State-Space Modeling Framework (Q5004352) (← links)
• When artificial parameter evolution gets real: particle filtering for time-varying parameter estimation in deterministic dynamical systems (Q5055689) (← links)
• Convergence analysis of a viscosity parameter recovery algorithm for the 2D Navier–Stokes equations (Q5072397) (← links)
• Using Monte Carlo Particle Methods to Estimate and Quantify Uncertainty in Periodic Parameters (Research) (Q5118673) (← links)
• Multiple linear regression model with stochastic design variables (Q5123588) (← links)
• A combined method to estimate parameters of neuron from a heavily noise-corrupted time series of active potential (Q5251428) (← links)
• Synchronization based system identification of an extended excitable system (Q5264318) (← links)
• Nonlinear systems identification by combining regression with bootstrap resampling (Q5264597) (← links)
• Identification of systems with unknown inputs using indirect input measurements (Q5280281) (← links)
• Statistical modelling of cell movement (Q6089176) (← links)
• Fourier series-based approximation of time-varying parameters in ordinary differential equations (Q6154905) (← links)
• Adaptive unscented Kalman filter for neuronal state and parameter estimation (Q6172485) (← links)
• Differential equations in data analysis (Q6602133) (← links)
• Divide and conquer: learning chaotic dynamical systems with multistep penalty neural ordinary differential equations (Q6641946) (← links)
• Application of particle swarm optimization for parameter estimation of the logistic map (Q6648338) (← links)