In this paper, we develop a new approach to the robust beamforming for general-rank signal models. Our method is based on the worst-case performance optimization using a semi-de n...
We introduce a distributed adaptive estimation algorithm operating in an ideal fully connected sensor network. The algorithm estimates node-specific signals at each node based on...
This paper presents a new sparse representation for acoustic signals which is based on a mixing model defined in the complex-spectrum domain (where additivity holds), and allows ...
Abstract. In this paper, we investigate the importance of the high frequencies in the problem of convolutive blind source separation (BSS) of speech signals. In particular, we focu...
The characterization of signals and images in manifolds often lead to efficient dimensionality reduction algorithms based on manifold distance computation for analysis or classi...