This paper focuses on the iterative identification problems for a class of Hammerstein nonlinear systems. By decomposing the system into two fictitious subsystems, a decomposition based least squares iterative algorithm is presented for estimating the parameter vectors in each subsystem. Moreover, a data filtering based decomposition least squares iterative algorithm is proposed. The simulation...

Parametric identification requires a good know-how and an accurate analysis. The most popular methods consist in using simply the least squares techniques because of their simplicity. However, these techniques are not intrinsically robust. An alternative consists in helping them with an appropriate data treatment. Another choice consists in applying a robust identification method. This paper fo...

A new unified modelling framework based on the superposition of additive submodels, functional components, and wavelet decompositions is proposed for nonlinear system identification. A nonlinear model, which is often represented using a multivariate nonlinear function, is initially decomposed into a number of functional components via the well known analysis of variance (ANOVA) expression, whic...

Globalization and advances in information technology represent both realities and opportunities for enterprises in the 21st century. This paper aims to broaden understanding of service innovation as a critical organizational capability through which the adoption of information technology influences firm performance. This study examines how the adoption of radio frequency identification (RFID) t...