Pages that link to "Item:Q2399133"

The following pages link to Recursive least squares and multi-innovation gradient estimation algorithms for bilinear stochastic systems (Q2399133):

Displaying 21 items.

• New gradient based identification methods for multivariate pseudo-linear systems using the multi-innovation and the data filtering (Q508358) (← links)
• Data filtering based maximum likelihood extended gradient method for multivariable systems with autoregressive moving average noise (Q1648051) (← links)
• Least-squares-based iterative and gradient-based iterative estimation algorithms for bilinear systems (Q1678371) (← links)
• Recursive parameter identification of the dynamical models for bilinear state space systems (Q1687334) (← links)
• The hierarchical iterative identification algorithm for multi-input-output-error systems with autoregressive noise (Q1687433) (← links)
• Decomposition-based gradient estimation algorithms for multivariate equation-error autoregressive systems using the multi-innovation theory (Q2003302) (← links)
• Recursive and iterative least squares parameter estimation algorithms for multiple-input-output-error systems with autoregressive noise (Q2003303) (← links)
• The maximum likelihood least squares based iterative estimation algorithm for bilinear systems with autoregressive moving average noise (Q2011872) (← links)
• Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise (Q2087500) (← links)
• Gradient estimation algorithms for the parameter identification of bilinear systems using the auxiliary model (Q2293618) (← links)
• Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise (Q2334210) (← links)
• Hierarchical stochastic gradient algorithm and its performance analysis for a class of bilinear-in-parameter systems (Q2400914) (← links)
• Recursive least squares and multi-innovation stochastic gradient parameter estimation methods for signal modeling (Q2400928) (← links)
• The gradient-based iterative estimation algorithms for bilinear systems with autoregressive noise (Q2411712) (← links)
• (Q3110529) (← 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)
• Decomposition-based recursive least squares identification methods for multivariate pseudo-linear systems using the multi-innovation (Q5027578) (← links)
• The filtering‐based maximum likelihood iterative estimation algorithms for a special class of nonlinear systems with autoregressive moving average noise using the hierarchical identification principle (Q5241002) (← links)
• Maximum likelihood based multi-innovation stochastic gradient identification algorithms for bilinear stochastic systems with ARMA noise (Q6498020) (← links)
• Data filtering-based recursive identification for an exponential autoregressive moving average model by using the multi-innovation theory (Q6609011) (← links)