This paper addresses the tracking capability of blind source separation algorithms for rapidly time-varying sensor or source positions. Based on a known algorithm for blind source ...
S. Wehr, Anthony Lombard, Herbert Buchner, Walter ...
Discovering a representation that allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can b...
In underdetermined blind source separation problems, it is common practice to exploit the underlying sparsity of the sources for demixing. In this work, we propose two sparse decom...
Deriving a thematically meaningful partition of an unlabeled document corpus is a challenging task. In this context, the use of document representations based on latent thematic ge...
In this paper we describe a methodology for model-based single channel separation of sounds. We present a sparse latent variable model that can learn sounds based on their distribu...
Paris Smaragdis, Bhiksha Raj, Madhusudana V. S. Sh...