Decentralized compression and predistribution via randomized gossiping
Proceedings of the 5th international conference on Information processing in sensor networks
Proceedings of the 5th international conference on Information processing in sensor networks
Universal distributed sensing via random projections
Proceedings of the 5th international conference on Information processing in sensor networks
Information fusion for wireless sensor networks: Methods, models, and classifications
ACM Computing Surveys (CSUR)
Bayesian compressive sensing and projection optimization
Proceedings of the 24th international conference on Machine learning
Compressed network monitoring for ip and all-optical networks
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Compressive sensing for multi-static scattering analysis
Journal of Computational Physics
Asymptotic achievability of the Cramér-Rao bound for noisy compressive sampling
IEEE Transactions on Signal Processing
Sparse reconstruction by separable approximation
IEEE Transactions on Signal Processing
A compressive sensing data acquisition and imaging method for stepped frequency GPRs
IEEE Transactions on Signal Processing
On the reconstruction of block-sparse signals with an optimal number of measurements
IEEE Transactions on Signal Processing
Sampling theorems for signals from the union of finite-dimensional linear subspaces
IEEE Transactions on Information Theory
Managing massive time series streams with multi-scale compressed trickles
Proceedings of the VLDB Endowment
Performance bounds on compressed sensing with Poisson noise
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Modified-CS: modifying compressive sensing for problems with partially known support
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
On sharp performance bounds for robust sparse signal recoveries
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
A neural network pruning approach based on compressive sampling
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Distributed analog linear coding of correlated Gaussian sources over multiple access channels
ISWCS'09 Proceedings of the 6th international conference on Symposium on Wireless Communication Systems
Comparison of SPARLS and RLS algorithms for adaptive filtering
SARNOFF'09 Proceedings of the 32nd international conference on Sarnoff symposium
Necessary and sufficient conditions for sparsity pattern recovery
IEEE Transactions on Information Theory
Hash-based identification of sparse image tampering
IEEE Transactions on Image Processing
Model-based compressive sensing for signal ensembles
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Distributed analog coding of correlated Gaussian sources
Allerton'09 Proceedings of the 47th annual Allerton conference on Communication, control, and computing
Data acquisition through joint compressive sensing and principal component analysis
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Block compressed sensing of images using directional transforms
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Model-based compressive sensing
IEEE Transactions on Information Theory
Compressive distilled sensing: sparse recovery using adaptivity in compressive measurements
Asilomar'09 Proceedings of the 43rd Asilomar conference on Signals, systems and computers
Sparse representation of medical images via compressed sensing using Gaussian scale mixtures
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Sparsity-regularized photon-limited imaging
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Compressed sensing performance bounds under Poisson noise
IEEE Transactions on Signal Processing
SPARLS: the sparse RLS algorithm
IEEE Transactions on Signal Processing
Compressive acquisition of dynamic scenes
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Toeplitz compressed sensing matrices with applications to sparse channel estimation
IEEE Transactions on Information Theory
An alternating minimization method for sparse channel estimation
LVA/ICA'10 Proceedings of the 9th international conference on Latent variable analysis and signal separation
A generalized cauchy distribution framework for problems requiring robust behavior
EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
Compressive sensing of underground structures using GPR
Digital Signal Processing
Learning with Structured Sparsity
The Journal of Machine Learning Research
Analysis of performance of palmprint matching with enforced sparsity
Digital Signal Processing
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Block-Based Compressed Sensing of Images and Video
Foundations and Trends in Signal Processing
Performance analysis of partial segmented compressed sampling
Signal Processing
Compression in wireless sensor networks: A survey and comparative evaluation
ACM Transactions on Sensor Networks (TOSN)
| Hi-index | 755.10 |
Recent results show that a relatively small number of random projections of a signal can contain most of its salient information. It follows that if a signal is compressible in some orthonormal basis, then a very accurate reconstruction can be obtained from random projections. This "compressive sampling" approach is extended here to show that signals can be accurately recovered from random projections contaminated with noise. A practical iterative algorithm for signal reconstruction is proposed, and potential applications to coding, analog-digital (A/D) conversion, and remote wireless sensing are discussed