Pages that link to "Item:Q2429064"

The following pages link to Maximum likelihood stochastic gradient estimation for Hammerstein systems with colored noise based on the key term separation technique (Q2429064):

Displaying 40 items.

• Recursive Bayesian algorithm with covariance resetting for identification of Box-Jenkins systems with non-uniformly sampled input data (Q308072) (← links)
• Hierarchical least squares algorithms for nonlinear feedback system modeling (Q328119) (← links)
• Auxiliary model based least squares identification method for a state space model with a unit time-delay (Q345433) (← links)
• Convergence properties of the least squares estimation algorithm for multivariable systems (Q345827) (← links)
• Auxiliary model based least squares parameter estimation algorithm for feedback nonlinear systems using the hierarchical identification principle (Q398298) (← links)
• A property of the eigenvalues of the symmetric positive definite matrix and the iterative algorithm for coupled Sylvester matrix equations (Q398374) (← links)
• Several gradient parameter estimation algorithms for dual-rate sampled systems (Q398410) (← links)
• Two recursive least squares parameter estimation algorithms for multirate multiple-input systems by using the auxiliary model (Q419419) (← links)
• Two-stage least squares based iterative identification algorithm for controlled autoregressive moving average (CARMA) systems (Q453817) (← links)
• Observable state space realizations for multivariable systems (Q453877) (← links)
• Maximum likelihood gradient-based iterative estimation algorithm for a class of input nonlinear controlled autoregressive ARMA systems (Q493928) (← links)
• Parameter estimation algorithms for Hammerstein output error systems using Levenberg-Marquardt optimization method with varying interval measurements (Q509499) (← links)
• An iterative least squares estimation algorithm for controlled moving average systems based on matrix decomposition (Q714591) (← links)
• Computation of matrix exponentials of special matrices (Q907552) (← links)
• A filtering based recursive least squares estimation algorithm for pseudo-linear auto-regressive systems (Q1659459) (← links)
• Modeling and identification of discrete-time nonlinear dynamic cascade systems with input hysteresis (Q1665581) (← links)
• Two-stage least squares based iterative estimation algorithm for CARARMA system modeling (Q1667765) (← links)
• Two identification methods for dual-rate sampled-data nonlinear output-error systems (Q1718153) (← links)
• Iterative system identification and controller design with an LMI-based framework: Windsurfer-like Approach (Q1760646) (← links)
• Least-squares parameter estimation algorithm for a class of input nonlinear systems (Q1760800) (← links)
• Three-stage recursive least squares parameter estimation for controlled autoregressive autoregressive systems (Q1789049) (← links)
• Gradient based iterative parameter identification for Wiener nonlinear systems (Q1789549) (← links)
• Extended stochastic gradient identification method for Hammerstein model based on approximate least absolute deviation (Q1793825) (← links)
• Maximum likelihood least squares identification method for input nonlinear finite impulse response moving average systems (Q1930955) (← links)
• Recursive computational formulas of the least squares criterion functions for scalar system identification (Q1991294) (← links)
• Combined state and least squares parameter estimation algorithms for dynamic systems (Q1991337) (← links)
• Parameter identification of systems with preload nonlinearities based on the finite impulse response model and negative gradient search (Q2017916) (← links)
• An interactive maximum likelihood estimation method for multivariable Hammerstein systems (Q2217617) (← links)
• Data filtering based multi-innovation extended gradient method for controlled autoregressive autoregressive moving average systems using the maximum likelihood principle (Q2228963) (← links)
• Newton iterative identification method for an input nonlinear finite impulse response system with moving average noise using the key variables separation technique (Q2259602) (← links)
• Least-squares-based iterative identification algorithm for Wiener nonlinear systems (Q2375585) (← links)
• A novel APSO-aided maximum likelihood identification method for Hammerstein systems (Q2435639) (← 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)
• 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)
• Some stochastic gradient algorithms for Hammerstein systems with piecewise linearity (Q2697720) (← links)
• Performance analysis of the auxiliary model-based least-squares identification algorithm for one-step state-delay systems (Q4903484) (← links)
• Parameter learning for the nonlinear system described by Hammerstein model with output disturbance (Q6580891) (← links)