Many clustering algorithms fail when dealing with high dimensional data. Principal component analysis (PCA) is a popular dimensionality reduction algorithm. However, it assumes a ...
The knowledge of the target speech presence probability in a mixture of signals captured by a speech communication system is of paramount importance in several applications includi...
Mehrez Souden, Jingdong Chen, Jacob Benesty, Sofi&...
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...
Independent Component Analysis is becoming a popular exploratory method for analysing complex data such as that from FMRI experiments. The application of such `model-free' me...
This article proposes a novel similarity measure between
vector sequences. Recently, a model-based approach was
introduced to address this issue. It consists in modeling
each se...