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...
Abstract. Joint diagonalization for ICA is often performed on the orthogonal group after a pre-whitening step. Here we assume that we only want to extract a few sources after pre-w...
Fabian J. Theis, Thomas P. Cason, Pierre-Antoine A...
Abstract. Binary Factor Analysis (BFA) is a typical problem of Independent Component Analysis (ICA) where the signal sources are binary. Parameter learning and model selection in B...
Abstract. In this paper we present a probabilistic algorithm which factorizes non-negative data. We employ entropic priors to additionally satisfy that user specified pairs of fac...
Paris Smaragdis, Madhusudana V. S. Shashanka, Bhik...
We propose a probabilistic model for the Independent Vector Analysis approach to blind deconvolution and derive an asymptotic Newton method to estimate the model by Maximum Likelih...
Jason A. Palmer, Kenneth Kreutz-Delgado, Scott Mak...