Pages that link to "Item:Q1663702"

The following pages link to Variable knot-based spline approximation recursive Bayesian algorithm for the identification of Wiener systems with process noise (Q1663702):

Displaying 7 items.

• Recursive Bayesian algorithm with covariance resetting for identification of Box-Jenkins systems with non-uniformly sampled input data (Q308072) (← links)
• Robust hierarchical identification of Wiener systems in the presence of dynamic disturbances (Q2181451) (← links)
• Identification of Wiener model with internal noise using a cubic spline approximation-Bayesian composite quantile regression algorithm (Q2290958) (← links)
• System identification of Wiener systems with B-spline functions using De Boor recursion (Q2872640) (← links)
• Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter (Q5026890) (← links)
• (Q5367944) (← links)
• The modified extended Kalman filter based recursive estimation for Wiener nonlinear systems with process noise and measurement noise (Q6073603) (← links)