Maximum likelihood hierarchical least squares-based iterative identification for dual-rate stochastic systems

Related Items (1)

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

Cites Work

Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
Robust fault tolerant tracking control for the multi-joint manipulator based on operator theory
Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems
Robust hierarchical identification of Wiener systems in the presence of dynamic disturbances
A recursive parameter estimation algorithm for modeling signals with multi-frequencies
Hierarchical recursive generalized extended least squares estimation algorithms for a class of nonlinear stochastic systems with colored noise
Recursive least squares and multi-innovation stochastic gradient parameter estimation methods for signal modeling
Aitken based modified Kalman filtering stochastic gradient algorithm for dual-rate nonlinear models
Adaptive parameter estimation for a general dynamical system with unknown states
Decomposition‐based multiinnovation gradient identification algorithms for a special bilinear system based on its input‐output representation
Parameter estimation for block‐oriented nonlinear systems using the key term separation
Stochastic average gradient algorithm for multirate FIR models with varying time delays using self‐organizing maps
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
Hierarchical Least Squares Identification for Linear SISO Systems With Dual-Rate Sampled-Data

This page was built for publication: Maximum likelihood hierarchical least squares-based iterative identification for dual-rate stochastic systems