Abstract
In Compressed Sensing (CS) framework, reconstruction of a signal relies on the knowledge of the sparse basis & measurement matrix used for sensing. Most of the studies so far focus on the application of CS in fields of images, radar, astronomy and Speech. This paper introduce new sensing matrix called orthogonal Symmetric Toeplitz Matrix (OSTM) generated with Binary, Ternary and PN sequence and shows detailed comparison of them with DCT Basis applied on 8 KHz sampled speech signal. Also it shows improved results of OSTM compared to Random, Bernoulli, Hadamard and Fourier Matrices. Performance of sensing matrices has been compared with Mean square error, Signal to noise ratio and Perceptual Evaluation of Speech Quality (PESQ) parameters.
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