Implementation of l1 Magic and One Bit Compressed Sensing Based on Linear Programming Using Excel

Author

Indukala, P.K. ; Lakshmi, K. ; Sowmya, V. ; Soman, K.P.

Author_Institution

Amrita Sch. of Eng., Center for Excellence in Comput. Eng. & Networking, Amrita Vishwa Vidyapeetham, Coimbatore, India

fYear

2012

fDate

9-11 Aug. 2012

Firstpage

69

Lastpage

72

Abstract

Compressed sensing helps in the reconstruction of sparse or compressible signals from small number of measurements. The sparse representation has great importance in modern signal processing. The main objective is to provide a strong understanding of the concept behind the theory of compressed sensing by using the key ideas from linear algebra. In this paper, the concept of compressed sensing is explained through an experiment formulated based on linear programming and solved using l1 magic and One bit compressed sensing methods in Excel.

Keywords

compressed sensing; linear algebra; linear programming; signal reconstruction; Excel; compressible signals reconstruction; l1 magic; linear algebra; linear programming; one bit compressed sensing methods; signal processing; sparse signals reconstruction; Compressed sensing; Linear programming; Presses; Sensors; Sparse matrices; Standards; Vectors; Compressed sensing; Excel; Linear Programming; One bit Compressed sensing; l1 Magic;

fLanguage

English

Publisher

ieee

Conference_Titel

Advances in Computing and Communications (ICACC), 2012 International Conference on

Conference_Location

Cochin, Kerala

Print_ISBN

978-1-4673-1911-9

Type

conf

DOI

10.1109/ICACC.2012.67

Filename

6305556