Pages that link to "Item:Q776148"

The following pages link to Data filtering based maximum likelihood gradient estimation algorithms for a multivariate equation-error system with ARMA noise (Q776148):

Displaying 20 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 extended gradient method for multivariable systems with autoregressive moving average noise (Q1648051) (← links)
• Maximum likelihood based recursive parameter estimation for controlled autoregressive ARMA systems using the data filtering technique (Q1660826) (← links)
• Maximum likelihood recursive least squares estimation for multivariate equation-error ARMA systems (Q1797200) (← links)
• Data filtering-based multi-innovation forgetting gradient algorithms for input nonlinear FIR-MA systems with piecewise-linear characteristics (Q2068227) (← links)
• Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory (Q2125313) (← links)
• Gradient-based parameter estimation for input nonlinear systems with ARMA noises based on the auxiliary model (Q2441975) (← links)
• Data filtering based stochastic gradient algorithms for multivariable CARAR-like systems (Q2846822) (← links)
• Maximum likelihood-based recursive least-squares estimation for multivariable systems using the data filtering technique (Q5025908) (← links)
• Recursive least-squares algorithm for a characteristic model with coloured noise by means of the data filtering technique (Q5028709) (← links)
• Partially coupled gradient estimation algorithm for multivariable equation‐error autoregressive moving average systems using the data filtering technique (Q5109084) (← links)
• Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear‐in‐parameter systems (Q6053700) (← links)
• Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion (Q6053746) (← links)
• Variational Bayesian identification for bilinear state space models with Markov‐switching time delays (Q6061263) (← links)
• Three‐stage forgetting factor stochastic gradient parameter estimation methods for a class of nonlinear systems (Q6061864) (← links)
• Maximum likelihood extended gradient‐based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity (Q6068317) (← links)
• Iterative parameter identification algorithms for the generalized time‐varying system with a measurable disturbance vector (Q6085140) (← links)
• A novel dynamic nonlinear partial least squares based on the cascade structure (Q6085143) (← links)
• Auxiliary model maximum likelihood gradient-based iterative identification for feedback nonlinear systems (Q6631782) (← links)
• Sliding window iterative identification for nonlinear closed-loop systems based on the maximum likelihood principle (Q6664769) (← links)