Pages that link to "Item:Q642909"

The following pages link to Parameter estimation with scarce measurements (Q642909):

Displaying 50 items.

• Least-squares based and gradient based iterative parameter estimation algorithms for a class of linear-in-parameters multiple-input single-output output error systems (Q2336626) (← links)
• A least squares identification algorithm for a state space model with multi-state delays (Q2339028) (← links)
• Signal modeling using the gradient search (Q2339039) (← links)
• Gradient-based iterative identification for MISO Wiener nonlinear systems: application to a glutamate fermentation process (Q2339054) (← links)
• A multi-innovation recursive least squares algorithm with a forgetting factor for Hammerstein CAR systems with backlash (Q2362602) (← links)
• Least-squares-based iterative identification algorithm for Wiener nonlinear systems (Q2375585) (← links)
• Least squares estimation for a class of non-uniformly sampled systems based on the hierarchical identification principle (Q2391798) (← links)
• Hierarchical stochastic gradient algorithm and its performance analysis for a class of bilinear-in-parameter systems (Q2400914) (← links)
• Particle filtering based parameter estimation for systems with output-error type model structures (Q2423919) (← 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)
• Filtering based recursive least squares algorithm for Hammerstein FIR-MA systems (Q2435673) (← links)
• An iterative algorithm for the generalized reflexive solutions of the general coupled matrix equations (Q2436137) (← links)
• Least squares algorithm for an input nonlinear system with a dynamic subspace state space model (Q2436150) (← 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)
• Fuzzy modeling of non-uniformly sampling nonlinear systems based on clustering method and convergence analysis (Q2661893) (← links)
• Short-time linear quadratic form technique for estimating fast-varying parameters in feedback loops (Q2814026) (← links)
• Observability under sampling for nonlinear systems (Q2821255) (← links)
• Least-squares-based iterative identification algorithm for Hammerstein nonlinear systems with non-uniform sampling (Q2855774) (← links)
• Robust and nonlinear control literature survey (No. 27) (Q2882419) (← links)
• Performance analysis of the auxiliary model-based least-squares identification algorithm for one-step state-delay systems (Q4903484) (← links)
• Robust economic model predictive control of nonlinear networked control systems with communication delays (Q5000699) (← links)
• Identification of Hammerstein–Wiener models with hysteresis front nonlinearities (Q5056575) (← links)
• Performance Analysis of The Auxiliary‐Model‐Based Multi‐Innovation Stochastic Newton Recursive Algorithm for Dual‐Rate Systems (Q5270472) (← links)
• Multi‐innovation gradient parameter estimation for multivariable systems based on the maximum likelihood principle (Q6053671) (← links)
• Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear‐in‐parameter systems (Q6053700) (← links)
• Accelerated identification algorithms for rational models based on the vector transformation (Q6053734) (← 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)
• Maximum likelihood extended gradient‐based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity (Q6068317) (← links)
• Modeling nonlinear systems using the tensor network B‐spline and the multi‐innovation identification theory (Q6069269) (← links)
• Multi‐innovation Newton recursive methods for solving the support vector machine regression problems (Q6071503) (← links)
• Identification of an ARX model with impulse noise using a variable step size information gradient algorithm based on the kurtosis and minimum Renyi error entropy (Q6082676) (← links)
• Modified particle filtering‐based robust estimation for a networked control system corrupted by impulsive noise (Q6082737) (← 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)
• Convergence analysis of the modified adaptive extended Kalman filter for the parameter estimation of a brushless DC motor (Q6092358) (← links)
• An efficient recursive identification algorithm for multilinear systems based on tensor decomposition (Q6092365) (← links)
• Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data (Q6099491) (← links)
• Gradient-based recursive parameter estimation for a periodically nonuniformly sampled-data Hammerstein-Wiener system based on the key-term separation (Q6494842) (← links)
• Iterative identification methods for a class of bilinear systems by using the particle filtering technique (Q6494849) (← links)
• Hierarchical recursive least squares algorithms for Hammerstein nonlinear autoregressive output-error systems (Q6495162) (← links)
• Identification of Wiener systems based on the variable forgetting factor multierror stochastic gradient and the key term separation (Q6495317) (← links)
• Identification and U-control of a state-space system with time-delay (Q6495624) (← links)
• Auxiliary model-based multi-innovation recursive identification algorithms for an input nonlinear controlled autoregressive moving average system with variable-gain nonlinearity (Q6495656) (← links)