Pages that link to "Item:Q876374"

The following pages link to Auxiliary model-based least-squares identification methods for Hammerstein output-error systems (Q876374):

Displaying 45 items.

• 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)
• Two-stage recursive least squares parameter estimation algorithm for output error models (Q1931035) (← links)
• Improved discrete techniques of time-delay and order estimation for large-scale interconnected nonlinear systems (Q1992430) (← links)
• Hierarchical recursive least squares parameter estimation of non-uniformly sampled Hammerstein nonlinear systems based on Kalman filter (Q2012124) (← links)
• Parameter identification of systems with preload nonlinearities based on the finite impulse response model and negative gradient search (Q2017916) (← links)
• Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory (Q2125313) (← links)
• Recursive least squares parameter estimation algorithm for dual-rate sampled-data nonlinear systems (Q2259606) (← links)
• A recursive parametric estimation algorithm of multivariable nonlinear systems described by Hammerstein mathematical models (Q2282370) (← links)
• Model recovery for Hammerstein systems using the auxiliary model based orthogonal matching pursuit method (Q2295093) (← links)
• Gradient-based iterative identification for MISO Wiener nonlinear systems: application to a glutamate fermentation process (Q2339054) (← links)
• System identification application using Hammerstein model (Q2363757) (← links)
• Least-squares-based iterative identification algorithm for Wiener nonlinear systems (Q2375585) (← links)
• Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems (Q2389435) (← links)
• Gradient based estimation algorithm for Hammerstein systems with saturation and dead-zone nonlinearities (Q2428877) (← links)
• Maximum likelihood stochastic gradient estimation for Hammerstein systems with colored noise based on the key term separation technique (Q2429064) (← links)
• A novel APSO-aided maximum likelihood identification method for Hammerstein systems (Q2435639) (← 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)
• Newton iterative identification for a class of output nonlinear systems with moving average noises (Q2436948) (← links)
• Gradient-based parameter estimation for input nonlinear systems with ARMA noises based on the auxiliary model (Q2441975) (← links)
• Iterative solutions of the generalized Sylvester matrix equations by using the hierarchical identification principle (Q2479168) (← links)
• Parameter identification of multi-input, single-output systems based on FIR models and least squares principle (Q2479192) (← links)
• Least squares based iterative identification algorithms for input nonlinear controlled autoregressive systems based on the auxiliary model (Q2517579) (← links)
• New identification method for Hammerstein models based on approximate least absolute deviation (Q2822267) (← links)
• Auxiliary model identification methods. Part B: input nonlinear output-error systems (Q2824139) (← links)
• Least-squares-based iterative identification algorithm for Hammerstein nonlinear systems with non-uniform sampling (Q2855774) (← links)
• Maximum likelihood parameter estimation algorithm for controlled autoregressive autoregressive models (Q2885561) (← links)
• (Q2984466) (← links)
• Auxiliary model based identification methods. part C: input nonlinear output-error autoregressive systems (Q3180776) (← links)
• Identification of cascade systems with backlash (Q3578762) (← links)
• Identification of Hammerstein models for control using ASYM (Q4543922) (← links)
• Instrument variable method based on nonlinear transformed instruments for Hammerstein system identification (Q4555759) (← links)
• Performance analysis of the auxiliary model-based least-squares identification algorithm for one-step state-delay systems (Q4903484) (← links)
• Adaptive Control Scheme for Large‐Scale Interconnected Systems Described by Hammerstein Models (Q5280223) (← links)
• Recursive identification for multi-input–multi-output Hammerstein–Wiener system (Q5383008) (← links)
• Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion (Q6053746) (← links)
• Instrumental variable‐based multi‐innovation gradient estimation for nonlinear systems with scarce measurements (Q6054508) (← links)
• Bias compensated stochastic gradient algorithm for identification of an ARX‐type nonlinear rational model and its application in modeling of the dynamic of the cellular toxicity (Q6063741) (← links)
• Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory (Q6069269) (← links)
• Iterative parameter identification algorithms for the generalized time‐varying system with a measurable disturbance vector (Q6085140) (← links)
• An efficient conjugate gradient based Cholesky CMA‐ES estimation algorithm for nonlinear systems (Q6117622) (← links)
• Separation identification approach for the <scp>Hammerstein‐Wiener</scp> nonlinear systems with process noise using correlation analysis (Q6154708) (← links)
• Parameter learning for the nonlinear system described by a class of Hammerstein models (Q6612059) (← links)