Compressed Sensing With Cross Validation

Compressed sensing (CS) decoding algorithms can efficiently recover an N -dimensional real-valued vector x to within a factor of its best k-term approximation by taking m = O(klogN/k) measurements y = Phi x . If the sparsity or approximate sparsity level of x were known, then this theoretical guaran...

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Veröffentlicht in:	IEEE transactions on information theory 2009-12, Vol.55 (12), p.5773-5782
1. Verfasser:	Ward, R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Applied sciences Approximation Approximation algorithms Best k -term approximation Coding, codes Compressed Compressed sensing compressed sensing (CS) Costs cross validation Decoding Detection Encoding encoding/decoding error estimates Estimates Estimating techniques Exact sciences and technology Information theory Information, signal and communications theory Johnson-Lindenstrauss (JL) lemma Mathematical analysis Mathematics Measurement measurements Pixel Quality assurance Signal and communications theory Signal processing algorithms Telecommunications and information theory Vectors Vectors (mathematics)
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