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» On sparse signal representations
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ICA
2010
Springer
13 years 6 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 6 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 10 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 6 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 10 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