Pages that link to "Item:Q4546915"
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The following pages link to Nonlinear time series modelling with the radial basis function-based state-dependent autoregressive model (Q4546915):
Displaying 14 items.
- Reduced state methods in nonlinear prediction (Q672815) (← links)
- Application of Bayesian trained RBF networks to nonlinear time-series modeling (Q948131) (← links)
- Radial basis function and related models: An overview (Q1350387) (← links)
- Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models (Q2247107) (← links)
- Parameter estimation for a class of radial basis function-based nonlinear time-series models with moving average noises (Q2656862) (← links)
- Exploiting the interpretability and forecasting ability of the RBF-AR model for nonlinear time series (Q2798518) (← links)
- A STUDY OF THE APPLICATION OF STATE-DEPENDENT MODELS IN NON-LINEAR TIME SERIES ANALYSIS (Q3218966) (← links)
- Structured parameter optimization method for the radial basis function-based state-dependent autoregressive model (Q4808250) (← links)
- Recursive methods for estimating the radial basis function‐based state‐dependent autoregressive model (Q4990449) (← links)
- Estimation of Nonparametric Autoregressive Time Series Models Under Dynamical Constraints (Q5467608) (← links)
- Forecasting warranty performance in the presence of the ‘maturing data’ phenomenon (Q5704613) (← links)
- Testing for nonlinearity in high-dimensional time series from continuous dynamics (Q5944258) (← links)
- Parameter identification of a nonlinear radial basis function‐based state‐dependent autoregressive network with autoregressive noise via the filtering technique and the multiinnovation theory (Q6082923) (← links)
- Hierarchical recursive Levenberg-Marquardt algorithm for radial basis function autoregressive models (Q6095646) (← links)
