In this paper we report our results concerning the study of multivariate functions of threshold-decomposed signals. In particular we show that multilinear tensor forms of the decomposed signal yield a...
Approximation networks combined with learning algorithms are being increasingly used to represent or approximate unknown mappings of multivariate functionals. Potential functions in general, and the s...
This paper describes a new spatio-temporal access method (SEST-Index) that combines two approaches for modeling spatio-temporal information: snapshots and events. This method makes it possible to not ...
We take some first steps in providing a synthetic theory of distributions. In particular, we are interested in the use of distribution theory as foundation, not just as tool, in the study of the wave ...
We take some first steps in providing a synthetic theory of distributions. In particular, we are interested in the use of distribution theory as foundation, not just as tool, in the study of the wave ...
A nonlinear population model with cross-diffusion terms for two competing species is studied analytically and numerically. Due to the cross-diffusion terms, the problem is strongly nonlinear and so, n...
A positivity-preserving numerical scheme for a strongly coupled cross-diffusion model for two competing species is presented, based on a semidiscretization in time. The variables are the population de...
. We present a new algorithm to search regular expressions, which is able to skip text characters. The idea is to determine the minimum length ` of a string matching the regular expression, manipulate...