Analyzing the Nonlinear System by Designing an Optimum Digital Filter named Hermitian-Wiener Filter

Qiaoyu Wang (Electrical and Computer Systems Engineering Department, Monash University, Melbourne, Victoria, Australia)
Kai Kang (Electrical and Computer Systems Engineering Department, Monash University, Melbourne, Victoria, Australia)
Jiayi Meng (Faculty of Arts, Melbourne University, Melbourne, Victoria, Australia)


The classical Wiener filter was engaged into identifying the linear structures, resulting in clear and incredible drawbacks in working with nonlinear integrated system. Currently, the Hermitian-Wiener system are suitable for unpredicted sub-system that consists of numerous and complex inputs. The system introduces a two-stage to analyze the subintervals where the output nonlinearities are noninvertible, through using the unknown orders and parameters. Finally, a practical strategy would be discussed to analyze the nonlinear parameters.


Hermitian-Wiener filter;Nonlinearity subsystems;Frequency domain;Wiener systems

Full Text:



[1] Brouri, A., Giri, F., Ikhouane, F., Chaoui, F. Z., Amdouri, O. Identification of hammerstein-wiener systems with backlash input nonlinearity bordered by straight lines. IFAC Proceedings Volumes, 2014, 47(3): 475-480.

[2] Wills, A., Schön, T. B., Ljung, L., Ninness, B. Identification of hammerstein–wiener models. Automatica, 2013, 49(1): 70-81.

[3] Brouri, A., Kadi, L., Slassi, S. Frequency identification of Hammerstein-Wiener systems with Backlash input nonlinearity. International Journal of Control, Automation and Systems, 2017, 15(5): 2222-2232.

[4] Hsu, Y. L., Wang, J. S. A Wiener-type recurrent neural network and its control strategy for nonlinear dynamic applications. Journal of Process Control, 2009,19(6): 942-953.

[5] Lacy, S. L., Erwin, R. S., Bernstein, D. S.. Identification of Wiener systems with known noninvertible nonlinearities. In Proceedings of the 2001 American Control Conference. (Cat. No. 01CH37148), IEEE,2001, 6: 4890-4895.

[6] Schoukens, M., Bai, E. W., Rolain, Y. Identification of hammerstein-wiener systems. IFAC Proceedings Volumes, 2012, 45(16): 274-279.

[7] Zhou, L., Li, X., Pan, F. Least-squares-based iterative identification algorithm for Wiener nonlinear systems. Journal of Applied Mathematics, 2013.

[8] Hunter, I. W., Korenberg, M. J. The identification of nonlinear biological systems: Wiener and Hammerstein cascade models. Biological cybernetics, 1986,55(2-3): 135-144.



  • There are currently no refbacks.
Copyright © 2020 Author(s)

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.