Compressed Sensing Reconstruction of an Audio signal using OMP
Journal: International Journal of Advanced Computer Research (IJACR) (Vol.5, No. 18)Publication Date: 2015-03-31
Authors : Shwetha A. Gangannawar; Saroja V. Siddmal;
Page : 75-79
Keywords : Compressive sensing; sparsity; measurement matrix and OMP.;
Abstract
Compressive sensing (CS) is an evolving technique for data acquisition that promises sampling a sparse signal from a far fewer measurements than its dimension. Compressive sensing enables a potentially large reduction in the sampling and computation cost for sensing signals that have sparse representation. The signal having sparse representation can be recovered from small set of linear, non-adaptive measurements. This paper mainly focuses on fixing threshold value for proper reconstruction of an audio signal. An audio signal is better reconstructed for the threshold value between (-0.02 to +0.02). Various performance parameters are measured which describe exact reconstruction of the signal. For proper reconstruction Orthogonal Matching Pursuit algorithm is used.
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Last modified: 2015-04-14 17:08:35