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JMLR
2012
11 years 11 months ago
Universal Measurement Bounds for Structured Sparse Signal Recovery
Standard compressive sensing results state that to exactly recover an s sparse signal in Rp , one requires O(s · log p) measurements. While this bound is extremely useful in prac...
Nikhil S. Rao, Ben Recht, Robert D. Nowak
ICASSP
2011
IEEE
13 years 7 days ago
A low-power implantable neuroprocessor on nano-FPGA for Brain Machine interface applications
This paper presents the implementation of a low-power and implantable neuroprocessor on low-cost nano-FPGA for data reduction and on-the-fly spike sorting in Brain Machine Interfa...
Fei Zhang, Mehdi Aghagolzadeh, Karim G. Oweiss
SIAMSC
2010
215views more  SIAMSC 2010»
13 years 6 months ago
A Fast Algorithm for Sparse Reconstruction Based on Shrinkage, Subspace Optimization, and Continuation
We propose a fast algorithm for solving the ℓ1-regularized minimization problem minx∈Rn µ x 1 + Ax − b 2 2 for recovering sparse solutions to an undetermined system of linea...
Zaiwen Wen, Wotao Yin, Donald Goldfarb, Yin Zhang
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 5 months ago
Real-time Robust Principal Components' Pursuit
In the recent work of Candes et al, the problem of recovering low rank matrix corrupted by i.i.d. sparse outliers is studied and a very elegant solution, principal component pursui...
Chenlu Qiu, Namrata Vaswani
SIAMIS
2011
13 years 3 months ago
Large Scale Bayesian Inference and Experimental Design for Sparse Linear Models
Abstract. Many problems of low-level computer vision and image processing, such as denoising, deconvolution, tomographic reconstruction or superresolution, can be addressed by maxi...
Matthias W. Seeger, Hannes Nickisch