All a b c d e f g h i j k l m n o p q r s t u v w x y z Other

Page 1

Displaying 1 – 13 of 13

Showing per page

A predictive method allowing the use of a single ionic model in numerical cardiac electrophysiology

M. Rioux, Y. Bourgault (2013)

ESAIM: Mathematical Modelling and Numerical Analysis - Modélisation Mathématique et Analyse Numérique

One of the current debate about simulating the electrical activity in the heart is the following: Using a realistic anatomical setting, i.e. realistic geometries, fibres orientations, etc., is it enough to use a simplified 2-variable phenomenological model to reproduce the main characteristics of the cardiac action potential propagation, and in what sense is it sufficient? Using a combination of dimensional and asymptotic analysis, together with the well-known Mitchell − Schaeffer model, it is shown...

High Resolution Tracking of Cell Membrane Dynamics in Moving Cells: an Electrifying Approach

R.A. Tyson, D.B.A. Epstein, K.I. Anderson, T. Bretschneider (2010)

Mathematical Modelling of Natural Phenomena

Cell motility is an integral part of a diverse set of biological processes. The quest for mathematical models of cell motility has prompted the development of automated approaches for gathering quantitative data on cell morphology, and the distribution of molecular players involved in cell motility. Here we review recent approaches for quantifying cell motility, including automated cell segmentation and tracking. Secondly, we present our own novel...

On determining unknown functions in differential systems, with an application to biological reactors

Éric Busvelle, Jean-Paul Gauthier (2003)

ESAIM: Control, Optimisation and Calculus of Variations

In this paper, we consider general nonlinear systems with observations, containing a (single) unknown function ϕ . We study the possibility to learn about this unknown function via the observations: if it is possible to determine the [values of the] unknown function from any experiment [on the set of states visited during the experiment], and for any arbitrary input function, on any time interval, we say that the system is “identifiable”. For systems without controls, we give a more or less complete...

On determining unknown functions in differential systems, with an application to biological reactors.

Éric Busvelle, Jean-Paul Gauthier (2010)

ESAIM: Control, Optimisation and Calculus of Variations

In this paper, we consider general nonlinear systems with observations, containing a (single) unknown function φ. We study the possibility to learn about this unknown function via the observations: if it is possible to determine the [values of the] unknown function from any experiment [on the set of states visited during the experiment], and for any arbitrary input function, on any time interval, we say that the system is “identifiable”. For systems without controls, we give a more or less complete...

Currently displaying 1 – 13 of 13

Page 1