Pages that link to "Item:Q1667765"

The following pages link to Two-stage least squares based iterative estimation algorithm for CARARMA system modeling (Q1667765):

Displaying 23 items.

• Several gradient-based iterative estimation algorithms for a class of nonlinear systems using the filtering technique (Q2346248) (← links)
• Least-squares-based iterative identification algorithm for Wiener nonlinear systems (Q2375585) (← links)
• Kalman filtering based gradient estimation algorithms for observer canonical state-space systems with moving average noises (Q2423917) (← links)
• Multistage least squares based iterative estimation for feedback nonlinear systems with moving average noises using the hierarchical identification principle (Q2435648) (← links)
• Filtering based recursive least squares algorithm for Hammerstein FIR-MA systems (Q2435673) (← links)
• Least squares algorithm for an input nonlinear system with a dynamic subspace state space model (Q2436150) (← links)
• Maximum likelihood Newton recursive and the Newton iterative estimation algorithms for Hammerstein CARAR systems (Q2436166) (← links)
• Parameter estimation for a multivariable state space system with \(d\)-step state-delay (Q2436802) (← links)
• Newton iterative identification for a class of output nonlinear systems with moving average noises (Q2436948) (← links)
• Iterative estimation methods for Hammerstein controlled autoregressive moving average systems based on the key-term separation principle (Q2439375) (← links)
• Least squares based iterative identification algorithms for input nonlinear controlled autoregressive systems based on the auxiliary model (Q2517579) (← links)
• Least-squares-based iterative identification algorithm for Hammerstein nonlinear systems with non-uniform sampling (Q2855774) (← links)
• A new linearization technique for minimax linear fractional programming (Q2935390) (← links)
• Recursive identification for multivariate autoregressive equation-error systems with autoregressive noise (Q5027843) (← 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)
• Consistency of the extended gradient identification algorithm for multi-input multi-output systems with moving average noises (Q5416435) (← links)
• Modified particle filtering‐based robust estimation for a networked control system corrupted by impulsive noise (Q6082737) (← links)
• Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data (Q6099491) (← links)
• Interval division and linearization algorithm for minimax linear fractional program (Q6140900) (← links)
• Multi-innovation gradient estimation algorithms for multivariate equation-error autoregressive moving average systems based on the filtering technique (Q6598653) (← links)