Skip to main content

Sparse Signal Analysis Using Ramanujan Sums

  • Conference paper
Intelligent Computing Theories and Technology (ICIC 2013)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7996))

Included in the following conference series:

Abstract

In this paper, we perform sparse signal analysis by using the Ramanujan Sums (RS). The RS are orthogonal in nature and therefore offer excellent energy conservation. Our analysis shows that the RS can compress the energy of a periodic impulse chain signal into fewer number of RS coefficients than the Fourier transform (FT). In addition, the RS are faster than the FT in computation time because we can calculate the RS basis functions only once and save them to a file. We can retrieve these RS basis functions for our calculation instead of computing them online. To process a signal of 128 samples, we spend 1.0 millisecond for the RS and 5.82 milliseconds for the FT by using our unoptimized Matlab code.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ramanujan, R.: On Certain Trigonometric Sums And Their Applications. Trans. Cambridge Philos. Soc. 22, 259–276 (1918)

    Google Scholar 

  2. Sugavaneswaran, L., Xie, S., Umapathy, K., Krishnan, S.: Time-frequency analysis via Ramanujan sums. IEEE Signal Processing Letters 19(6), 352–355 (2012)

    Article  Google Scholar 

  3. Planat, M.: Ramanujan sums for signal processing of low frequency noise. Phys. Rev. E. 66 (2002)

    Google Scholar 

  4. Samadi, S., Ahmad, M.O., Swamy, M.N.S.: Ramanujan sums and discrete fourier transform. IEEE Signal Processing Letters 12(4), 293–296 (2005)

    Article  Google Scholar 

  5. Mainardi, L.T., Pattini, L., Cerutti, S.: Application of the Ramanujan Fourier transform for the analysis of secondary structure content in amino acid sequences. Meth. Inf. Med. 46(2), 126–129 (2007)

    Google Scholar 

  6. Mainardi, L.T., Bertinelli, M., Sassi, R.: Analysis of T-wave alternans using the Ramanujan Sums. Computer in Cardiology 35, 605–608 (2008)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Chen, G., Krishnan, S., Liu, W., Xie, W. (2013). Sparse Signal Analysis Using Ramanujan Sums. In: Huang, DS., Jo, KH., Zhou, YQ., Han, K. (eds) Intelligent Computing Theories and Technology. ICIC 2013. Lecture Notes in Computer Science(), vol 7996. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39482-9_52

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-39482-9_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-39481-2

  • Online ISBN: 978-3-642-39482-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics