: In this paper, two nonlinear optimization methods for the identification of nonlinear systems are compared. Both methods estimate all the parameters of a polynomial nonlinear sta...
Anne Van Mulders, Johan Schoukens, Marnix Volckaer...
System identification of plants with binary-valued output observations is of importance in understanding modeling capability and limitations for systems with limited sensor inform...
Abstract. In many cases, complex system behaviors are naturally modeled as nonlinear differential equations. However, these equations are often hard to analyze because of "sti...
Abstract. Hybrid cc is a constraint programming language suitable for modeling, controlling and simulating hybrid systems, i.e. systems with continuous and discrete state changes. ...
This paper adresses the variance quantification problem for system identification based on the prediction error framework. The role of input and model class selection for the auto-...