Pages that link to "Item:Q1687334"

The following pages link to Recursive parameter identification of the dynamical models for bilinear state space systems (Q1687334):

Displaying 50 items.

• Reprint of ``A bilinear differential forms approach to parametric structured state-space modelling'' (Q305632) (← links)
• Fast recursive identification of state space models via exploitation of displacement structure (Q1314744) (← links)
• A hierarchical least squares identification algorithm for Hammerstein nonlinear systems using the key term separation (Q1643235) (← links)
• Multi-step-length gradient iterative algorithm for equation-error type models (Q1647799) (← links)
• Data filtering based maximum likelihood extended gradient method for multivariable systems with autoregressive moving average noise (Q1648051) (← links)
• Particle swarm optimization iterative identification algorithm and gradient iterative identification algorithm for Wiener systems with colored noise (Q1654314) (← links)
• Adaptive gradient-based iterative algorithm for multivariable controlled autoregressive moving average systems using the data filtering technique (Q1654319) (← links)
• Combined state and parameter estimation for a bilinear state space system with moving average noise (Q1661792) (← links)
• Recursive parameter estimation algorithm for multivariate output-error systems (Q1661829) (← links)
• Collaborative linear dynamical system identification by scarce relevant/irrelevant observations (Q1710964) (← 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)
• Hierarchical gradient- and least squares-based iterative algorithms for input nonlinear output-error systems using the key term separation (Q2030993) (← links)
• Data filtering-based multi-innovation forgetting gradient algorithms for input nonlinear FIR-MA systems with piecewise-linear characteristics (Q2068227) (← links)
• Hierarchical multi-innovation stochastic gradient identification algorithm for estimating a bilinear state-space model with moving average noise (Q2087500) (← links)
• Model recovery for multi-input signal-output nonlinear systems based on the compressed sensing recovery theory (Q2125313) (← links)
• An interactive maximum likelihood estimation method for multivariable Hammerstein systems (Q2217617) (← links)
• Recursive identification of bilinear time-delay systems through the redundant rule (Q2291091) (← links)
• Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise (Q2334210) (← links)
• Aitken based modified Kalman filtering stochastic gradient algorithm for dual-rate nonlinear models (Q2416724) (← 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)
• (Q2994131) (← links)
• Recursive identification of bilinear systems (Q3757756) (← links)
• (Q3998857) (← links)
• Recursive identification of certain structured time-varying state–space models (Q4367843) (← links)
• Hierarchical identification of lifted state-space models for general dual-rate systems (Q4590455) (← 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 identification methods for rational models (Q5025848) (← links)
• Maximum likelihood iterative identification approaches for multivariable equation-error moving average systems (Q5026619) (← links)
• Hierarchical parameter and state estimation for bilinear systems (Q5026681) (← links)
• Parameter estimation for a special class of nonlinear systems by using the over-parameterisation method and the linear filter (Q5026890) (← links)
• Decomposition-based recursive least squares identification methods for multivariate pseudo-linear systems using the multi-innovation (Q5027578) (← links)
• Recursive identification for multivariate autoregressive equation-error systems with autoregressive noise (Q5027843) (← 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)
• Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window (Q6042570) (← links)
• Three‐stage least squares‐based iterative estimation algorithms for bilinear state‐space systems based on the bilinear state estimator (Q6049911) (← links)
• Hierarchical maximum likelihood generalized extended stochastic gradient algorithms for bilinear‐in‐parameter systems (Q6053700) (← links)
• Filtering‐based multi‐innovation recursive identification methods for input nonlinear systems with piecewise‐linear nonlinearity based on the optimization criterion (Q6053746) (← links)