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NIPS
1998
13 years 6 months ago
Coding Time-Varying Signals Using Sparse, Shift-Invariant Representations
A common way to represent a time series is to divide it into shortduration blocks, each of which is then represented by a set of basis functions. A limitation of this approach, ho...
Michael S. Lewicki, Terrence J. Sejnowski
ICIP
2003
IEEE
14 years 6 months ago
Redundant representation with complex wavelets: how to achieve sparsity
Overcomplete transforms, like the Dual-Tree Complex Wavelet Transform, offer more flexible signal representations than critically-sampled transforms, due to their properties of sh...
Nick G. Kingsbury, Tanya Reeves
ICASSP
2007
IEEE
13 years 11 months ago
Quantized Sparse Approximation with Iterative Thresholding for Audio Coding
Sparse coding is a new field in signal processing with possible applications to source coding. In this paper we present a new method that combines the problems of sparse signal a...
Mehrdad Yaghoobi, Thomas Blumensath, Mike E. Davie...
SPEECH
2011
12 years 11 months ago
Auditory-inspired sparse representation of audio signals
This article deals with the generation of auditory-inspired spectro-temporal features aimed at audio coding. To do so, we first generate sparse audio representations we call spik...
Ramin Pichevar, Hossein Najaf-Zadeh, Louis Thibaul...
ICASSP
2011
IEEE
12 years 8 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad