Despite their effectiveness for robust speech processing, missing data techniques are vulnerable to errors in the classification of the input speech signal’s time-frequency poi...
Owing to the stochastic nature of discrete processes such as photon counts in imaging, a variety of real-world data are well modeled as Poisson random variables whose means are in...
Compressive Sensing (CS) uses a relatively small number of non-traditional samples in the form of randomized projections to reconstruct sparse or compressible signals. The Hough t...
Ali Cafer Gurbuz, James H. McClellan, Justin K. Ro...
to appear in Proc. IEEE Int’l Conf. on Acoustics, Speech, and Signal Processing, March, 2008 High-dynamic-range medical images take intensity values which cannot be visualized o...
It is well known that high-dimensional nearest-neighbor retrieval is very expensive. Many signal processing methods suffer from this computing cost. Dramatic performance gains can...