MATEC Web of Conferences
Volume 22, 2015International Conference on Engineering Technology and Application (ICETA 2015)
|Number of page(s)||5|
|Section||Information and Communication Technology|
|Published online||09 July 2015|
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
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.