Approximability models and optimal system identification

Modeling gene regulatory networks: Classical models, optimal perturbation for identification of network

Deep understanding of molecular biology has allowed emergence of new technologies like DNA decryption.  On the other hand, advancements of molecular biology have made manipulation of genetic systems simpler than ever; this promises extraordinary progress in biological, medical and biotechnological applications.  This is not an unrealistic goal since genes which are regulated by gene regulatory ...

Identification of Wiener models using optimal local linear models

The Wiener model is a versatile nonlinear block oriented model structure for miscellaneous applications. In this paper a method for identifying the parameters of such a model using optimal local linear models is presented. The linear model part is represented by a discretetime transfer function and the non-linear characteristic is represented by piece-wise linear functions. Parameter estimation...

System Identification Using Fuzzy Models

Combining Models in System Identification

Patching different kinds of models obtained from experimental data is considered in this paper. The problem of combining different experiments and models is analysed. As a related issue, iteratively improving models and combining models for control oriented identification is investigated. A simulated example is given to illustrate the approach. Copyright  2000 IFAC

Robust optimal experiment design for system identification

This paper develops the idea of min-max robust experiment design for dynamic system identification. The idea of min-max experiment design has been explored in the statistics literature. However, the technique is virtually unknown by the engineering community and, accordingly, there has been little prior work on examining its properties when applied to dynamic system identification. This paper i...