Modern networks are highly variable and, as a result, source coders are commonly used under conditions that they were not designed for. We address this problem with a source-codin...
In the last decade various time- and frequency-domain algorithms were derived to blindly identify acoustic systems. One of these algorithms is the multichannel Newton (MCN) algori...
We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
Nonnegative matrix factorization (NMF) is a widely-used tool for obtaining low-rank approximations of nonnegative data such as digital images, audio signals, textual data, financ...
This paper considers two problems in sparse filter design, the first involving a least-squares constraint on the frequency response, and the second a constraint on signal-to-noi...