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» Support Recovery of Sparse Signals
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ISNN
2007
Springer
15 years 5 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li
CISS
2011
IEEE
14 years 3 months ago
The Restricted Isometry Property for block diagonal matrices
—In compressive sensing (CS), the Restricted Isometry Property (RIP) is a powerful condition on measurement operators which ensures robust recovery of sparse vectors is possible ...
Han Lun Yap, Armin Eftekhari, Michael B. Wakin, Ch...
ICASSP
2010
IEEE
14 years 12 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...
CISS
2008
IEEE
15 years 6 months ago
Information theory based estimator of the number of sources in a sparse linear mixing model
—In this paper we present an Information Theoretic Estimator for the number of sources mutually disjoint in a linear mixing model. The approach follows the Minimum Description Le...
Radu Balan
ICASSP
2011
IEEE
14 years 3 months ago
Weighted and structured sparse total least-squares for perturbed compressive sampling
Solving linear regression problems based on the total least-squares (TLS) criterion has well-documented merits in various applications, where perturbations appear both in the data...
Hao Zhu, Georgios B. Giannakis, Geert Leus