Two identification algorithms, an iterative least-squares and a recursive least-squares, are developed for Hammerstein nonlinear systems with memoryless nonlinear blocks and linear …
In this paper, we propose a blind approach to the sampled Hammerstein–Wiener model identification. By using the blind approach, it is shown that all internal variables can be …
The present bibliography represents a comprehensive list of references on nonlinear system identification and its applications in signal processing, communications, and biomedical …
F Ding, Y Shi, T Chen - Systems & Control Letters, 2007 - Elsevier
The difficulty in identification of a Hammerstein (a linear dynamical block following a memoryless nonlinear block) nonlinear output-error model is that the information vector in …
The aim of this book is to show that the nonparametric regression can be successfully applied to system identification and how much can be achieved in this way. It gathers what …
This monograph systematically presents the existing identification methods of nonlinear systems using the block-oriented approach It surveys various known approaches to the …
EW Bai, D Li - IEEE Transactions on automatic control, 2004 - ieeexplore.ieee.org
The convergence of the iterative identification algorithm for the Hammerstein system has been an open problem for a long time. In this paper, a detailed study is carried out and …
This paper studies a method for the identification of Hammerstein models based on least squares support vector machines (LS-SVMs). The technique allows for the determination of …
I Goethals, K Pelckmans, JAK Suykens… - IEEE Transactions on …, 2005 - ieeexplore.ieee.org
This paper presents a method for the identification of multiple-input-multiple-output (MIMO) Hammerstein systems for the goal of prediction. The method extends the numerical …