Computational Statistics & Data Analysis
Performance analysis of multi-innovation gradient type identification methods
Automatica (Journal of IFAC)
Adaptive Digital Control of Hammerstein Nonlinear Systems with Limited Output Sampling
SIAM Journal on Control and Optimization
Extended stochastic gradient identification algorithms for Hammerstein-Wiener ARMAX systems
Computers & Mathematics with Applications
Blind maximum likelihood identification of Hammerstein systems
Automatica (Journal of IFAC)
Reconstruction of continuous-time systems from their non-uniformly sampled discrete-time systems
Automatica (Journal of IFAC)
Identification for multirate multi-input systems using the multi-innovation identification theory
Computers & Mathematics with Applications
Multi-innovation stochastic gradient algorithms for multi-input multi-output systems
Digital Signal Processing
The residual based interactive least squares algorithms and simulation studies
Computers & Mathematics with Applications
Blind maximum-likelihood identification of wiener systems
IEEE Transactions on Signal Processing
Brief paper: Least squares based iterative identification for a class of multirate systems
Automatica (Journal of IFAC)
Gradient based and least-squares based iterative identification methods for OE and OEMA systems
Digital Signal Processing
Convergence of stochastic gradient estimation algorithm for multivariable ARX-like systems
Computers & Mathematics with Applications
Auxiliary model-based RELS and MI-ELS algorithm for Hammerstein OEMA systems
Computers & Mathematics with Applications
Several multi-innovation identification methods
Digital Signal Processing
Multiinnovation least-squares identification for system modeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on game theory
Gradient-based iterative parameter estimation for Box-Jenkins systems
Computers & Mathematics with Applications
Identification methods for Hammerstein nonlinear systems
Digital Signal Processing
Parameter estimation with scarce measurements
Automatica (Journal of IFAC)
Parameter Identification and Intersample Output Estimation for Dual-Rate Systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Identifying chaotic systems using Wiener and Hammerstein cascade models
Mathematical and Computer Modelling: An International Journal
Auxiliary model based multi-innovation algorithms for multivariable nonlinear systems
Mathematical and Computer Modelling: An International Journal
Mathematical and Computer Modelling: An International Journal
Computers & Mathematics with Applications
Mathematics and Computers in Simulation
Observable state space realizations for multivariable systems
Computers & Mathematics with Applications
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This paper considers the identification problems of Hammerstein finite impulse response moving average (FIR-MA) systems using the maximum likelihood principle and stochastic gradient method based on the key term separation technique. In order to improve the convergence rate, a maximum likelihood multi-innovation stochastic gradient algorithm is presented. The simulation results show that the proposed algorithms can effectively estimate the parameters of the Hammerstein FIR-MA systems.