Change Point Discovery is a basic algorithm needed in many time series mining applications including rule discovery, motif discovery, casual analysis, etc. Several techniques for c...
One of the main problems that we have to face when visiting public or official buildings (i.e hospitals or public administrations) is the lack of information and signs that can gui...
A decision support system model is described to advise nature park managers. It applies dynamic modelling techniques to relate abiotic characteristics of a site over time to specie...
The process of knowledge discovery from databases is a knowledge intensive, highly user-oriented practice, thus has recently heralded the development of ontology-incorporated data ...
Abstract. This work aims to improve an existing time series forecasting algorithm –LBF– by the application of frequent episodes techniques as a complementary step to the model....
Abstract. The Matrix-Pencil approach to blind source separation estimates the mixing matrix from the Generalized Eigenvalue Decomposition (GEVD), or Exact Joint Diagonalization, of...
Underdetermined source separation is often carried out by modeling time-frequency source coefficients via a fixed sparse prior. This approach fails when the number of active sourc...
The problem of removing white zero-mean Gaussian noise from an image is an interesting inverse problem to be investigated in this paper through sparse and redundant representations...
We consider a method for solving the permutation problem in blind source separation (BSS) by the frequency-domain independent component analysis (FD-ICA) by using phase linearity o...