Nonlinear block-oriented systems, including the Hammerstein, Wiener and feedbacknonlinear systems have attracted considerable research interest both from the industrial and academic environments (Bai, 1998), (Greblicki, 1989), (Latawiec, 2004), (Latawiec et al., 2003), (Latawiec et al., 2004), (Pearson & Pottman, 2000). It is well known that orthonormal basis functions (OBF) (Bokor et al., 1999...

In this paper, non iterative algorithms for the identification of (multivariable) nonlinear systems consisting of the interconnection of LTI systems and static nonlinearities are presented. The proposed algorithms are numerically robust, since they are based only on least squares estimation and singular value decomposition. Three different block-oriented nonlinear models are considered in this ...

Nonlinearities provide a neverending challenge to systems and control. We savor linear systems since we have a good understanding of how they behave, and there is much we can do to analyze and predict their performance. As we move away from linearity, we need to scrutinize each nonlinearity that we encounter to assess its benefi t or detriment in terms of what we wish to achieve. The first issu...

　A new approach is introduced to estimate the formal information of neurons. Formal Information, mainly discusses about the aspects of the response that is related to the stimulus. Estimation is based on introducing a mathematical nonlinear model with Hammerstein-Wiener system estimator. This method of system identification consists of three blocks to completely describe the nonlinearity of inp...

Over the last two decades, there has been a growing interest in the use of orthonormal basis filters (OBF) for developing dynamic black box models. When compared with the conventional approach, a substantial dimensionality reduction can be achieved through OBF parameterization. Moreover, the orthonormal filters, because of their similarity to the Padé approximation, can model systems that exhib...

The existing results show the applicability of Over-Parameterized Model based Hammerstein-Wiener model identification methods. However, it requires to estimate extra parameters and performer a low rank approximation step. Therefore, may give rise unnecessarily high variance in parameter estimates for highly nonlinear systems, especially using small noisy data set. To overcome this corruptive ph...

Power amplifiers (PAs) are inherently nonlinear elements and digital predistortion is a highly cost-effective approach to linearize them. Although most existing architectures assume that the PA has a memoryless nonlinearity, memory effects of the PAs in many applications ,such as wideband code-division multiple access (WCDMA) or orthogonal frequency-division multiplexing (OFDM), can no longer b...