Sparse Component Analysis is a relatively young technique that relies upon a representation of signal occupying only a small part of a larger space. Mixtures of sparse components ...
In this paper, we propose a novel method for blind source separation (BSS) based on time-frequency sparseness (TF) that can estimate the number of sources and time-frequency masks,...
We consider the problem of diagnosing performance problems in distributed system and networks given end-to-end performance measurements provided by test transactions, or probes. C...
It was discovered recently that sparse decomposition by signal dictionaries results in dramatic improvement of the qualities of blind source separation. We exploit sparse decompos...
The problem of blindly separating signal mixtures with fewer mixture components than independent signal sources is mathematically ill-defined, and requires suitable prior informat...