Publication Type:

Conference Proceedings


International Conference on Advances in Computing and Communications, ICACC 2012, IEEE, Kochi, Kerala, p.69-72 (2012)





Compressive sensing, Excel, Linear algebra, Linear programming, Modern signal processing, Signal reconstruction, Sparse representation


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. © 2012 IEEE.


cited By (since 1996)0; Conference of org.apache.xalan.xsltc.dom.DOMAdapter@5a6879b ; Conference Date: org.apache.xalan.xsltc.dom.DOMAdapter@7810d402 Through org.apache.xalan.xsltc.dom.DOMAdapter@18cf0ce3; Conference Code:93547

Cite this Research Publication

P. K. Indukala, Lakshmi, K., Sowmya V., and Dr. Soman K. P., “Implementation of ℓ 1 magic and one bit compressed sensing based on linear programming using excel”, International Conference on Advances in Computing and Communications, ICACC 2012. IEEE, Kochi, Kerala, pp. 69-72, 2012.