You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
23 January 2017The fast algorithm of spark in compressive sensing
Compressed Sensing (CS) is an advanced theory on signal sampling and reconstruction. In CS theory, the reconstruction condition of signal is an important theory problem, and spark is a good index to study this problem. But the computation of spark is NP hard. In this paper, we study the problem of computing spark. For some special matrixes, for example, the Gaussian random matrix and 0-1 random matrix, we obtain some conclusions. Furthermore, for Gaussian random matrix with fewer rows than columns, we prove that its spark equals to the number of its rows plus one with probability 1. For general matrix, two methods are given to compute its spark. One is the method of directly searching and the other is the method of dual-tree searching. By simulating 24 Gaussian random matrixes and 18 0-1 random matrixes, we tested the computation time of these two methods. Numerical results showed that the dual-tree searching method had higher efficiency than directly searching, especially for those matrixes which has as much as rows and columns.
Meihua Xie andFengxia Yan
"The fast algorithm of spark in compressive sensing", Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103224J (23 January 2017); https://doi.org/10.1117/12.2265341
The alert did not successfully save. Please try again later.
Meihua Xie, Fengxia Yan, "The fast algorithm of spark in compressive sensing," Proc. SPIE 10322, Seventh International Conference on Electronics and Information Engineering, 103224J (23 January 2017); https://doi.org/10.1117/12.2265341