Automated Inference of Excitable Cell Models as Hybrid Automata.
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
In this paper, we explore from an experimental point of view the possibilities
and limitations of the new HYCGE learning algorithm for hybrid automata.
As an example of a practical application, we study the algorithm’s performance
on learning the behaviour of the action potential in excitable cells, specifically
the Hodgkin-Huxley model of a squid giant axon, the Luo-Rudy model of a
guinea pig ventricular cell, and the Entcheva model of a neonatal rat ventricular
cell. The validity and accuracy of the algorithm is also visualized through
Place, publisher, year, edition, pages
2013. , 29 p.
Engineering and Technology Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-143330OAI: oai:DiVA.org:kth-143330DiVA: diva2:706235
Meinke, Karl, Professor
Olsson, Mårten, Professor