Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6421108 | Applied Mathematics and Computation | 2014 | 7 Pages |
Abstract
This paper proposes a generalized extended stochastic gradient (GESG) algorithm for estimating the parameters of a class of Wiener nonlinear autoregressive moving average systems using the gradient search. In order to improve the convergence rates of the GESG algorithm, a multi-innovation GESG algorithm is derived. The simulation results indicate that the proposed algorithms can effectively estimate the parameters of a class of output nonlinear systems.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Yuanbiao Hu, Baolin Liu, Qin Zhou,