Pages that link to "Item:Q1654319"

The following pages link to Adaptive gradient-based iterative algorithm for multivariable controlled autoregressive moving average systems using the data filtering technique (Q1654319):

Displaying 29 items.

• Gradient-based iterative identification methods for multivariate pseudo-linear moving average systems using the data filtering (Q333157) (← links)
• Least squares based iterative parameter estimation algorithm for multivariable controlled ARMA system modelling with finite measurement data (Q636441) (← links)
• Data filtering based maximum likelihood extended gradient method for multivariable systems with autoregressive moving average noise (Q1648051) (← links)
• State space model identification of multirate processes with time-delay using the expectation maximization (Q1717533) (← links)
• Gradient-based iterative identification method for multivariate equation-error autoregressive moving average systems using the decomposition technique (Q1717535) (← links)
• Hierarchical Newton iterative parameter estimation of a class of input nonlinear systems based on the key term separation principle (Q1723012) (← links)
• Moving horizon estimation for multirate systems with time-varying time-delays (Q1730085) (← links)
• The filtering based parameter identification for bilinear-in-parameter systems (Q1757521) (← links)
• Maximum likelihood recursive least squares estimation for multivariate equation-error ARMA systems (Q1797200) (← links)
• Auxiliary model based recursive generalized least squares identification algorithm for multivariate output-error autoregressive systems using the decomposition technique (Q1797205) (← links)
• Quasi gradient-based inversion-free iterative algorithm for solving a class of the nonlinear matrix equations (Q2203811) (← links)
• Modeling a nonlinear process using the exponential autoregressive time series model (Q2308132) (← links)
• Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise (Q2334210) (← links)
• Kalman filtering based gradient estimation algorithms for observer canonical state-space systems with moving average noises (Q2423917) (← links)
• Particle filtering based parameter estimation for systems with output-error type model structures (Q2423919) (← links)
• Fitting the exponential autoregressive model through recursive search (Q2423988) (← links)
• Data filtering based stochastic gradient algorithms for multivariable CARAR-like systems (Q2846822) (← links)
• Hierarchical Newton and least squares iterative estimation algorithm for dynamic systems by transfer functions based on the impulse responses (Q5025821) (← links)
• Maximum likelihood-based recursive least-squares estimation for multivariable systems using the data filtering technique (Q5025908) (← links)
• Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter (Q5026890) (← links)
• Recursive identification for multivariate autoregressive equation-error systems with autoregressive noise (Q5027843) (← links)
• Partially coupled gradient estimation algorithm for multivariable equation‐error autoregressive moving average systems using the data filtering technique (Q5109084) (← links)
• The innovation algorithms for multivariable state‐space models (Q5128848) (← links)
• Highly computationally efficient state filter based on the delta operator (Q5240975) (← links)
• On some parameter estimation algorithms for the nonlinear exponential autoregressive model (Q5240985) (← links)
• Maximum likelihood gradient identification for multivariate equation‐error moving average systems using the multi‐innovation theory (Q5240987) (← links)
• State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors (Q5241000) (← 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)
• Multi-innovation gradient estimation algorithms for multivariate equation-error autoregressive moving average systems based on the filtering technique (Q6598653) (← links)