In this contribution, new online EM algorithms are proposed to perform inference in general hidden Markov models. These algorithms update the parameter at some deterministic times ...
Independent component analysis (ICA) is possibly the most widespread approach to solve the blind source separation (BSS) problem. Many different algorithms have been proposed, tog...
Jarkko Ylipaavalniemi, Nima Reyhani, Ricardo Vig&a...
As nonnegative tensor factorization (NTF) is particularly useful for the problem of underdetermined linear transform model, we performed NTF on the EEG data recorded from 14 electr...
Fengyu Cong, Anh Huy Phan, Piia Astikainen, Qibin ...
Abstract. The use of high level information in source separation algorithms can greatly constrain the problem and lead to improved results by limiting the solution space to semanti...
We consider an extension of ICA and BSS for separating mutually dependent and independent components from two related data sets. We propose a new method which first uses canonical...
Non-negative spectrogram factorization algorithms such as probabilistic latent component analysis (PLCA) have been shown to be quite powerful for source separation. When training d...
A novel tensor decomposition called pattern or P-decomposition is proposed to make it possible to identify replicating structures in complex data, such as textures and patterns in ...
Anh Huy Phan, Andrzej Cichocki, Petr Tichavsk&yacu...
Abstract. Missing data in corrupted audio recordings poses a challenging problem for audio signal processing. In this paper we present an approach that allows us to estimate missin...
We consider the Independent Subspace Analysis problem from the point of view of contrast functions, showing that contrast functions are able to partially solve the ISA problem. Tha...