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ICASSP
2011
IEEE
12 years 11 months ago
Deterministic compressed-sensing matrices: Where Toeplitz meets Golay
Recently, the statistical restricted isometry property (STRIP) has been formulated to analyze the performance of deterministic sampling matrices for compressed sensing. In this pa...
Kezhi Li, Cong Ling, Lu Gan
ICASSP
2008
IEEE
14 years 2 months ago
Wavelet-domain compressive signal reconstruction using a Hidden Markov Tree model
Compressive sensing aims to recover a sparse or compressible signal from a small set of projections onto random vectors; conventional solutions involve linear programming or greed...
Marco F. Duarte, Michael B. Wakin, Richard G. Bara...
CSR
2006
Springer
13 years 11 months ago
Window Subsequence Problems for Compressed Texts
Given two strings (a text t of length n and a pattern p) and a natural number w, window subsequence problems consist in deciding whether p occurs as a subsequence of t and/or findi...
Patrick Cégielski, Irène Guessarian,...
CDC
2010
IEEE
154views Control Systems» more  CDC 2010»
13 years 2 months ago
Concentration of measure inequalities for compressive Toeplitz matrices with applications to detection and system identification
In this paper, we derive concentration of measure inequalities for compressive Toeplitz matrices (having fewer rows than columns) with entries drawn from an independent and identic...
Borhan Molazem Sanandaji, Tyrone L. Vincent, Micha...
ICIP
2006
IEEE
14 years 9 months ago
An Architecture for Compressive Imaging
Compressive Sensing is an emerging field based on the revelation that a small group of non-adaptive linear projections of a compressible signal contains enough information for rec...
Michael B. Wakin, Jason N. Laska, Marco F. Duarte,...