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

Abstract EN

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.