Least-Squares-Based Iterative Identification Algorithm for Wiener Nonlinear Systems

Lincheng Zhou, Xiangli Li and Feng Pan

Journal of Applied Mathematics, 2013, vol. 2013, 1-6

Abstract:

This paper focuses on the identification problem of Wiener nonlinear systems. The application of the key-term separation principle provides a simplified form of the estimated parameter model. To solve the identification problem of Wiener nonlinear systems with the unmeasurable variables in the information vector, the least-squares-based iterative algorithm is presented by replacing the unmeasurable variables in the information vector with their corresponding iterative estimates. The simulation results indicate that the proposed algorithm is effective.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnljam:565841

DOI: 10.1155/2013/565841

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