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» On sparse signal representations
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ICA
2010
Springer
13 years 5 months ago
SMALLbox - An Evaluation Framework for Sparse Representations and Dictionary Learning Algorithms
SMALLbox is a new foundational framework for processing signals, using adaptive sparse structured representations. The main aim of SMALLbox is to become a test ground for explorati...
Ivan Damnjanovic, Matthew E. P. Davies, Mark D. Pl...
ICASSP
2010
IEEE
13 years 5 months ago
Approximate nearest neighbors using sparse representations
A new method is introduced that makes use of sparse image representations to search for approximate nearest neighbors (ANN) under the normalized inner-product distance. The approa...
Joaquin Zepeda, Ewa Kijak, Christine Guillemot
ICASSP
2011
IEEE
12 years 9 months ago
Optical MEMS image enhancement with sparse signal representation
This paper describes a complete low-complexity imaging system based on a single MEMS scanning mirror and a single photodetector, together with customized image enhancement algorit...
Ganchi Zhang, Li Li, Vladimir Stankovic, Lina Stan...
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 5 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
ICASSP
2011
IEEE
12 years 9 months ago
Dictionary learning of convolved signals
Assuming that a set of source signals is sparsely representable in a given dictionary, we show how their sparse recovery fails whenever we can only measure a convolved observation...
Daniele Barchiesi, Mark D. Plumbley