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ICASSP
2008
IEEE
14 years 3 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
14 years 18 days 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 3 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...
MICRO
2008
IEEE
139views Hardware» more  MICRO 2008»
14 years 3 months ago
Adaptive data compression for high-performance low-power on-chip networks
With the recent design shift towards increasing the number of processing elements in a chip, high-bandwidth support in on-chip interconnect is essential for low-latency communicat...
Yuho Jin, Ki Hwan Yum, Eun Jung Kim
ICIP
2006
IEEE
14 years 10 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,...