Least squares based and gradient based iterative identification for Wiener nonlinear systems

Authors:
Dongqing Wang;Feng Ding
Affiliations:
College of Automation Engineering, Qingdao University, Qingdao 266071, PR China;School of IoT Engineering, Jiangnan University, Wuxi 214122, PR China
Venue:
Signal Processing
Year:
2011

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Abstract

This paper derives a least squares-based and a gradient-based iterative identification algorithms for Wiener nonlinear systems. These methods separate one bilinear cost function into two linear cost functions, estimating directly the parameters of Wiener systems without re-parameterization to generate redundant estimates. The simulation results confirm that the proposed two algorithms are valid and the least squares-based iterative algorithm has faster convergence rates than the gradient-based iterative algorithm.