Construction of Deterministic Measurements Matrix Using Decimated Legendre Sequences
College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China
* Corresponding author: firstname.lastname@example.org
This paper proposed and constructed a new class of deterministic measurements matrix by using decimated binary Legendre sequences for convolutional Compressed Sensing. The author proves that when the measurement matrix is constructed by a random subsampling, it can offer a stable sparse reconstruction. Besides, the simulation results shows that when a deterministic subsampler is used, the proposed matrix can also guarantee the stable reconstruction as good as random Gaussian or Bernoulli matrixes do, which are commonly used in CS.
Key words: convolutional compressed sensing / Legendre sequences / RIP / coherence
© Owned by the authors, published by EDP Sciences, 2015
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