Filtering-based recursive least squares estimation approaches for multivariate equation-error systems by using the multiinnovation theory

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Auxiliary model-based iterative estimation algorithms for nonlinear systems using the covariance matrix adaptation strategy

Cites Work

Unnamed Item
Recursive least squares algorithm and gradient algorithm for Hammerstein-Wiener systems using the data filtering
The expected discounted penalty function under a renewal risk model with stochastic income
A hierarchical least squares identification algorithm for Hammerstein nonlinear systems using the key term separation
On spectrally positive Lévy risk processes with Parisian implementation delays in dividend payments
Recursive parameter estimation algorithm for multivariate output-error systems
Tensor network alternating linear scheme for MIMO Volterra system identification
Spectrally negative Lévy risk model under Erlangized barrier strategy
State space model identification of multirate processes with time-delay using the expectation maximization
Moving horizon estimation for multirate systems with time-varying time-delays
Piecewise reproducing kernel-based symmetric collocation approach for linear stationary singularly perturbed problems
Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems
A recursive parameter estimation algorithm for modeling signals with multi-frequencies
Reproducing kernel function-based Filon and Levin methods for solving highly oscillatory integral
Optimal periodic dividend and capital injection problem for spectrally positive Lévy processes
An extension of Paulsen-Gjessing's risk model with stochastic return on investments
Weighted parameter estimation for Hammerstein nonlinear ARX systems
MULTIVARIATE AR SYSTEMS AND MIXED FREQUENCY DATA: G-IDENTIFIABILITY AND ESTIMATION
Differentially Private MIMO Filtering for Event Streams
A Regularized Variable Projection Algorithm for Separable Nonlinear Least Squares Problems
Two‐stage auxiliary model gradient‐based iterative algorithm for the input nonlinear controlled autoregressive system with variable‐gain nonlinearity
Adaptive parameter estimation for a general dynamical system with unknown states
Recursive parameter estimation methods and convergence analysis for a special class of nonlinear systems
Robust adaptive control of nonlinearly parametrized multivariable systems with unmatched disturbances
Parameter estimation for block‐oriented nonlinear systems using the key term separation
The innovation algorithms for multivariable state‐space models
Lattice-Filter-Based Multivariate Autoregressive Spectral Estimation With Joint Model Order and Estimation Bandwidth Adaptation
Highly computationally efficient state filter based on the delta operator
State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors
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
Three‐stage forgetting factor stochastic gradient parameter estimation methods for a class of nonlinear systems
Maximum likelihood extended gradient‐based estimation algorithms for the input nonlinear controlled autoregressive moving average system with variable‐gain nonlinearity

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