Matrix computations (3rd ed.)
System identification (2nd ed.): theory for the user
System identification (2nd ed.): theory for the user
Brief paper: Iterative identification of Hammerstein systems
Automatica (Journal of IFAC)
Vector least-squares solutions for coupled singular matrix equations
Journal of Computational and Applied Mathematics
Some new connections between matrix products for partitioned and non-partitioned matrices
Computers & Mathematics with Applications
Multi-innovation stochastic gradient algorithms for multi-input multi-output systems
Digital Signal Processing
Adaptive Filtering Prediction and Control
Adaptive Filtering Prediction and Control
Gradient based and least-squares based iterative identification methods for OE and OEMA systems
Digital Signal Processing
Performance analysis of estimation algorithms of nonstationary ARMA processes
IEEE Transactions on Signal Processing
Gradient-based iterative parameter estimation for Box-Jenkins systems
Computers & Mathematics with Applications
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
Computers & Mathematics with Applications
Identification methods for Hammerstein nonlinear systems
Digital Signal Processing
Parameter estimation with scarce measurements
Automatica (Journal of IFAC)
A geometric approach to the linear modelling
CSS'11 Proceedings of the 5th WSEAS international conference on Circuits, systems and signals
Computers & Mathematics with Applications
Mathematics and Computers in Simulation
Observable state space realizations for multivariable systems
Computers & Mathematics with Applications
Mathematical and Computer Modelling: An International Journal
Auxiliary model based multi-innovation algorithms for multivariable nonlinear systems
Mathematical and Computer Modelling: An International Journal
Identification for the second-order systems based on the step response
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
Parameter estimation for nonlinear dynamical adjustment models
Mathematical and Computer Modelling: An International Journal
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A least squares based iterative identification algorithm is developed for Box-Jenkins models (or systems). The proposed iterative algorithm can produce highly accurate parameter estimation compared with recursive approaches. The basic idea of the proposed iterative method is to adopt the interactive estimation theory: the parameter estimates relying on unknown variables are computed by using the estimates of these unknown variables which are obtained from the preceding parameter estimates. The numerical example indicates that the proposed iterative algorithm has fast convergence rates compared with the gradient based iterative algorithm.