Computer Science – Information Theory
Scientific paper
2011-10-23
Computer Science
Information Theory
Scientific paper
In many data acquisition systems it is common to observe signals whose amplitudes have been clipped. We present two new algorithms for recovering a clipped signal by leveraging the model assumption that the underlying signal is sparse in the frequency domain. Both algorithms employ ideas commonly used in the field of Compressive Sensing; the first is a modified version of Reweighted $\ell_1$ minimization, and the second is a modification of a simple greedy algorithm known as Trivial Pursuit. An empirical investigation shows that both approaches can recover signals with significant levels of clipping
Wakin Michael B.
Weinstein Alejandro J.
No associations
LandOfFree
Recovering a Clipped Signal in Sparseland does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Recovering a Clipped Signal in Sparseland, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Recovering a Clipped Signal in Sparseland will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-526918