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ICASSP
2010
IEEE
13 years 6 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 1 months 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 6 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 1 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