MATHICSE Technical Report : Numerical approximation of parametrized problems in cardiac electrophysiology by a local reduced basis method
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Nonlinear dynamical systems have been used in many disciplines to model complex behaviors, including biological motor control, robotics, perception, economics, traffic prediction, and neuroscience. While often the unexpected emergent behavior of nonlinear ...
In this Master thesis we aim at studying some physiological and computational aspects of the excitation-contraction mechanisms in the heart muscle. This phenomenon exhibits many complexities at different spatio-temporal scales. The relevance and applicabil ...
Nonlinear modeling of coaxial microhelicopters is studied. All equations are derived using a Lagrangian approach and simplified aerodynamics assumptions so that all parameters have a physical meaning; there is no “black box.” The model is constructed with ...
In Control System Theory, the study of continuous-time, finite dimensional, underdetermined systems of ordinary differential equations is an important topic. Classification of systems in different categories is a natural initial step to the analysis of a g ...
In the present paper, an optimal control problem constrained by the tridomain equations in electrocardiology is investigated. The state equations consisting in a coupled reaction-diffusion system modelling the propagation of the intracellular and extracell ...
The R package bclust is useful for clustering high-dimensional continuous data. The package uses a parametric spike-and-slab Bayesian model to downweight the effect of noise variables and to quantify the importance of each variable in agglomerative cluster ...
In this paper we address the problem of detecting and localizing objects that can be both seen and heard, e.g., people. This may be solved within the framework of data clustering. We propose a new multimodal clustering algorithm based on a Gaussian mixture ...
This work addresses the problem of reducing the time between query submission and results output in a retrieval system. The goal is achieved by considering only a database fraction as small as possible during the retrieval process. Our approach is based on ...
We present an algorithm for clustering sets of detected interest points into groups that correspond to visually distinct structure. Through the use of a suitable colour and texture representation, our clustering method is able to identify keypoints that be ...
We propose to apply statistical clustering algorithms on a three-dimensional profile of red blood cells (RBCs) obtained through digital holographic microscopy (DHM). We show that two classes of RBCs stored for 14 and 38 days can be effectively classified. ...