Affiliation:
1. Wuxi Institute of Technology
2. Jiangnan University
Abstract
A new parameter estimation method is introduced for dual-rate Wiener systems. The method uses the finite input response model and a stochastic gradient algorithm to estimate the parameters of the finite input response model. The origin parameters can be computed by the estimated parameters. Simulation studies of dual-rate Wiener systems identification are included.
Publisher
Trans Tech Publications, Ltd.
Reference12 articles.
1. D.Q. Wang, F. Ding, Least squares based and gradient based iterative identification for Wiener nonlinear systems, Signal Processing 91 (5) (2011) 1182-1189.
2. X.L. Hu, H.F. Chen, Strong consistence of recursive identification for Wiener systems, Automatic 41 (11) (2005) 1905-(1916).
3. J. Chen, Y. Zhang, F. Ding, Least squares based iterative parameter estimation for output nonlinear systems with piece-wise nonlinearities, in: 2011 Chinese Control Conference, July 22-24, 2011 Yantai China 1438-1441.
4. D.Q. Wang, Y.Y. Chu, F. Ding, Identification methods for Wiener nonlinear systems based on the least squares and gradient iterations, 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, December 16-18, 2009, Shanghai China 3632-3636.
5. B. Yu, Y. Shi, H. Huang, filtering for multirate systems using lifted models, Circuit Systems and Signal Processing 27 (5) (2008) 699-711.