Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):
C. Hametner, S. Jakubek:
"Neuro-Fuzzy Modelling Using a Logistic Discriminant Tree";
Vortrag: American Control Conference 2007,
New York City, USA;
11.07.2007
- 13.07.2007; in: "Proceedings of the 2007 American Control Conference",
(2007),
ISBN: 1-4244-0989-6;
Paper-Nr. WeB04.6,
6 S.
Kurzfassung englisch:
An algorithm for nonlinear static and dynamic
identification using Takagi-Sugeno Fuzzy Models is presented.
For practical applications the incorporation of prior knowledge
and the interpretability of the local models is of great interest.
Using a tree structured algorithm in combination with the
distinction between the input arguments for the consequents and
for the premises the nonlinear optimisation is performed in an
efficient way. The axis oblique decomposition of the partition
space is based on an Expectation-Maximisation (EM) algorithm.
Simulation results demonstrate the capabilities of the proposed
concept.
Schlagworte:
Takagi-Sugeno Fuzzy Models, nonlinear system identification, discriminant tree, Expectation-Maximisation
Erstellt aus der Publikationsdatenbank der Technischen Universität Wien.