Publications in Scientific Journals:
M. Kozek, S. Sinanovic:
"Identification of Wiener Models Using Optimal Local Linear Models";
Simulation Modelling Practice and Theory (invited),
16
(2008),
8;
1055
- 1066.
English abstract:
Identification of a Wiener model using optimal local linear models (LLMs) is presented. The model consists of a discrete-time transfer function and piece-wise linear functions. Parameter estimation as well as partitioning of the LLMs is simultaneously accomplished by the algorithm. The optimality is threefold: First, each local model is linear in the parameters, thus leading to an optimal solution. Second, the model size of each LLM is adaptively optimized using a Chi-squared criterion, explicitly incorporating the measurement noise level. Third, the resulting model has a minimum of parameters for a given performance. Simulation results document that the output noise is balanced with the systems nonlinearity.
Keywords:
Nonlinear identification; Wiener model; Optimality; Local linear models.
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1016/j.simpat.2008.05.012
Created from the Publication Database of the Vienna University of Technology.