“Compressive Sampling in Sparse and Non Large Signal Sets”

AGUSTÍN MAILING; BRUNO CERNUSCHI FRÍAS

Rosario, Argentina

Congreso; XIII Reunión de Trabajo en Procesamiento de la Información y Control, RPIC 2009, 16 al 18 de Septiembre de 2009, Rosario, Argentina, ISBN 950-665-340-2, pp. 995-998.; 2009

Universidad Nacional de Rosario

In this work we analyze the practicalproblem with the bounds on the numberof samples needed to recover a sparse signalfrom its samples. On one hand the constrainton the size of the sample vector containing allthe information needed to successfully reconstructthe original signal does not depend onthe size of the original signal but on the sparsenessof the signal set. On the other hand, theless complex reconstruction from the data sampleimposes a constraint between all these values.Unfortunately, this constraint makes senseonly for large signal spaces.