Pages that link to "Item:Q2399050"

The following pages link to Filtering-based multistage recursive identification algorithm for an input nonlinear output-error autoregressive system by using the key term separation technique (Q2399050):

Displaying 28 items.

• The filtering based auxiliary model generalized extended stochastic gradient identification for a multivariate output-error system with autoregressive moving average noise using the multi-innovation theory (Q776143) (← links)
• Data filtering based maximum likelihood gradient estimation algorithms for a multivariate equation-error system with ARMA noise (Q776148) (← links)
• Bias correction-based recursive estimation for dual-rate output-error systems with sampling noise (Q831574) (← links)
• Hierarchical least squares identification for feedback nonlinear equation-error systems (Q1989304) (← links)
• Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems (Q2181393) (← links)
• Auxiliary variable-based identification algorithms for uncertain-input models (Q2193610) (← links)
• A recursive parameter estimation algorithm for modeling signals with multi-frequencies (Q2193644) (← links)
• Recursive identification of bilinear time-delay systems through the redundant rule (Q2291091) (← links)
• Gradient estimation algorithms for the parameter identification of bilinear systems using the auxiliary model (Q2293618) (← links)
• A recursive least squares parameter estimation algorithm for output nonlinear autoregressive systems using the input-output data filtering (Q2412488) (← links)
• Combined estimation of the parameters and states for a multivariable state‐space system in presence of colored noise (Q5000698) (← links)
• Separable multi‐innovation stochastic gradient estimation algorithm for the nonlinear dynamic responses of systems (Q5003429) (← links)
• Hierarchical parameter and state estimation for bilinear systems (Q5026681) (← links)
• Modelling and identification of nonlinear cascade systems with backlash input and static output nonlinearities (Q5861070) (← links)
• Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion (Q6053746) (← links)
• Maximum likelihood least squares‐based iterative methods for output‐error bilinear‐parameter models with colored noises (Q6078915) (← links)
• Data filtering‐based parameter estimation algorithms for a class of nonlinear systems with colored noises (Q6081010) (← links)
• Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data (Q6099491) (← links)
• Separable synthesis gradient estimation methods and convergence analysis for multivariable systems (Q6099494) (← links)
• Recursive identification of errors-in-variables systems based on the correlation analysis (Q6135540) (← links)
• Filtered auxiliary model recursive generalized extended parameter estimation methods for Box–Jenkins systems by means of the filtering identification idea (Q6193184) (← links)
• Recursive search-based identification algorithms for the exponential autoregressive time series model with coloured noise (Q6598712) (← links)
• Hierarchical multi-innovation generalised extended stochastic gradient methods for multivariable equation-error autoregressive moving average systems (Q6598747) (← links)
• Recursive parameter estimation and its convergence for bilinear systems (Q6598822) (← links)
• Improved least-squares identification for multiple-output non-linear stochastic systems (Q6598862) (← links)
• Parameter learning for the nonlinear system described by a class of Hammerstein models (Q6612059) (← links)
• Parameter estimation methods of linear continuous-time time-delay systems from multi-frequency response data (Q6612083) (← links)
• Hierarchical gradient-based iterative parameter estimation algorithms for a nonlinear feedback system based on the hierarchical identification principle (Q6652739) (← links)