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ICASSP
2010
IEEE
13 years 5 months ago
Adaptive compressed sensing - A new class of self-organizing coding models for neuroscience
Sparse coding networks, which utilize unsupervised learning to maximize coding efficiency, have successfully reproduced response properties found in primary visual cortex [1]. Ho...
William K. Coulter, Cristopher J. Hillar, Guy Isle...
CORR
2011
Springer
155views Education» more  CORR 2011»
13 years 14 days ago
Reconciling Compressive Sampling Systems for Spectrally-sparse Continuous-time Signals
The Random Demodulator (RD) and the Modulated Wideband Converter (MWC) are two recently proposed compressed sensing (CS) techniques for the acquisition of continuous-time spectral...
Michael A. Lexa, Mike E. Davies, John S. Thompson
ICMCS
2010
IEEE
191views Multimedia» more  ICMCS 2010»
13 years 4 months ago
Disparity-compensated compressed-sensing reconstruction for multiview images
In a multiview-imaging setting, image-acquisition costs could be substantially diminished if some of the cameras operate at a reduced quality. Compressed sensing is proposed to ef...
Maria Trocan, Thomas Maugey, James E. Fowler, B&ea...
CORR
2010
Springer
133views Education» more  CORR 2010»
13 years 5 months ago
Nonuniform Sparse Recovery with Gaussian Matrices
Compressive sensing predicts that sufficiently sparse vectors can be recovered from highly incomplete information. Efficient recovery methods such as 1-minimization find the sparse...
Ulas Ayaz, Holger Rauhut
SIAMIS
2011
13 years 15 days 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