Scientific computation is an area of research dedicated to the study of adapted numerical methods for solving specific applied
problems; it relies heavily on complexity theory and algorithms which are rapidly developing fields of computer science.
Topics of interest in scientific computation include matrix computation, continuous methods for ordinary differential
equations, interpolants for Runge-Kutta-Nystrom pairs, stability of fluid flows, nondestructive eddy current testing,
application of the Fatou-Julia iteration theory in dielectric spectroscopy, high precision polynomial rootfinder by matrix
methods, and applications of wavelets in signal and image processing. Heavy use is made of Matlab, Mathematica, Maple, and Fluent.
Ongoing research projects include image processing by means of singular value
decomposition (SVD) multiresolution analysis, weighted truncated SVD,
and neural networks with multiwavelets;
audio signal processing and music, solutions of nonlinear partial differential
equations by means of wavelets, application of complex zonal polynomials
in maximizing the bandwidth of multiple input multiple output (MIM0) signal;
Continuous and discrete wavelets are used for pipe system diagonosis and leak detection by unsteady-state tests.

Mise à jour/ update : 2004.05.05