Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1703273 | Applied Mathematical Modelling | 2015 | 9 Pages |
Abstract
This paper considers parameter estimation problems of Hammerstein finite impulse response moving average (FIR-MA) systems. In order to provide highly accurate parameter estimates and improve the convergence rate, a data filtering based multi-innovation extended stochastic gradient algorithm is presented to estimate the parameters of Hemmerstein FIR-MA systems by using the current innovation and past innovations. The simulation results show that the proposed algorithm can effectively estimate the parameters of the Hammerstein FIR-MA systems.
Related Topics
Physical Sciences and Engineering
Engineering
Computational Mechanics
Authors
Ziyun Wang, Yan Wang, Zhicheng Ji,