Pages that link to "Item:Q1989304"

The following pages link to Hierarchical least squares identification for feedback nonlinear equation-error systems (Q1989304):

Displaying 22 items.

• Hierarchical least squares algorithms for nonlinear feedback system modeling (Q328119) (← links)
• Auxiliary model based least squares parameter estimation algorithm for feedback nonlinear systems using the hierarchical identification principle (Q398298) (← links)
• Hierarchical least squares algorithms for single-input multiple-output systems based on the auxiliary model (Q614326) (← links)
• Hierarchical least squares identification for Hammerstein nonlinear controlled autoregressive systems (Q736348) (← links)
• The hierarchical iterative identification algorithm for multi-input-output-error systems with autoregressive noise (Q1687433) (← links)
• Data filtering-based multi-innovation forgetting gradient algorithms for input nonlinear FIR-MA systems with piecewise-linear characteristics (Q2068227) (← links)
• \(\mathscr{H}_-\) index for Itô stochastic systems with Poisson jump (Q2068234) (← links)
• Parameter estimation for nonlinear Volterra systems by using the multi-innovation identification theory and tensor decomposition (Q2071236) (← links)
• Multi-innovation gradient estimation algorithms and convergence analysis for feedback nonlinear equation-error moving average systems (Q2096137) (← links)
• Design of fractional hierarchical gradient descent algorithm for parameter estimation of nonlinear control autoregressive systems (Q2098687) (← links)
• An interactive maximum likelihood estimation method for multivariable Hammerstein systems (Q2217617) (← links)
• Multistage least squares based iterative estimation for feedback nonlinear systems with moving average noises using the hierarchical identification principle (Q2435648) (← links)
• System identification. part G: hierarchical identification principle and methods (Q2860153) (← links)
• (Q4289035) (← links)
• Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements (Q6054508) (← links)
• Wiener–Hammerstein nonlinear system identification using spectral analysis (Q6061100) (← links)
• Overall recursive least squares and overall stochastic gradient algorithms and their convergence for feedback nonlinear controlled autoregressive systems (Q6063758) (← links)
• Bias-compensated least squares and fuzzy PSO based hierarchical identification of errors-in-variables Wiener systems (Q6111221) (← links)
• A new adaptive identification framework for nonlinear multi-input multi-output systems under colored noise (Q6135577) (← links)
• Distributed learning-based visual coverage control of multiple mobile aerial agents (Q6494989) (← links)
• Two-stage gradient-based iterative algorithms for the fractional-order nonlinear systems by using the hierarchical identification principle (Q6496211) (← links)
• Identification of nonlinear system with time delay based on wavelet packet decomposition and Gaussian kernel GMDH network (Q6577124) (← links)