Scheduled System Maintenance on May 29th, 2015:
IEEE Xplore will be upgraded between 11:00 AM and 10:00 PM EDT. During this time there may be intermittent impact on performance. We apologize for any inconvenience.
By Topic

Parameter estimation for a pancreatic β-cell model by gradient-descent learning with line search

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Iwasa, Y. ; Dept. of Electr. Eng., Osaka Univ., Japan ; Doi, S. ; Kumagai, S.

Generation processes of action potentials in a single neuron are described by Hodgkin-Huxley (HH)-type equations [1,2]. HH-type equations can describe electrical activities of various cells as well as neurons. It requires difficult physiological experiments to construct a model as HH-type equations. Doya et al. [3,4] proposed a method to estimate several parameters of HH-type equations using gradient-descent learning method in which many parameters can be estimated by the measurement of membrane potential only without further physiological experiments. In the present paper, we show the method of Doya et al. can be applied to the parameter estimation of pancreatic β-cell model which has a complicated bursting waveform.

Published in:

Biomedical Engineering, 2003. IEEE EMBS Asian-Pacific Conference on

Date of Conference:

20-22 Oct. 2003