Table of Contents Author Guidelines Submit a Manuscript
Journal of Applied Mathematics
Volume 2013 (2013), Article ID 804640, 8 pages
http://dx.doi.org/10.1155/2013/804640
Research Article

Splitting Matching Pursuit Method for Reconstructing Sparse Signal in Compressed Sensing

1The School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi 710049, China
2The MOE Key Lab for Intelligent and Networked Systems, The School of Electronic and Information Engineering, Xian Jiaotong University, Xi’an, Shaanxi 710049, China

Received 14 March 2013; Accepted 16 April 2013

Academic Editor: Xianxia Zhang

Copyright © 2013 Liu Jing et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. S. S. Chen, D. L. Donoho, and M. A. Saunders, “Atomic decomposition by basis pursuit,” SIAM Journal on Scientific Computing, vol. 20, no. 1, pp. 33–61, 1998. View at Publisher · View at Google Scholar · View at MathSciNet
  2. S. Boyd and L. Vandenberghe, Convex Optimization, Cambridge University Press, Cambridge, UK, 2004. View at MathSciNet
  3. J. A. Tropp and S. J. Wright, “Computational methods for sparse solution of linear inverse problems,” Proceedings of the IEEE, vol. 98, no. 6, pp. 948–958, 2010. View at Publisher · View at Google Scholar · View at Scopus
  4. S. G. Mallat and Z. Zhang, “Matching pursuits with time-frequency dictionaries,” IEEE Transactions on Signal Processing, vol. 41, no. 12, pp. 3397–3415, 1993. View at Publisher · View at Google Scholar · View at Scopus
  5. J. A. Tropp, “Greed is good: algorithmic results for sparse approximation,” IEEE Transactions on Information Theory, vol. 50, no. 10, pp. 2231–2242, 2004. View at Publisher · View at Google Scholar · View at MathSciNet
  6. D. Needell and R. Vershynin, “Uniform uncertainty principle and signal recovery via regularized orthogonal matching pursuit,” Foundations of Computational Mathematics, vol. 9, no. 3, pp. 317–334, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  7. W. Dai and O. Milenkovic, “Subspace pursuit for compressive sensing signal reconstruction,” IEEE Transactions on Information Theory, vol. 55, no. 5, pp. 2230–2249, 2009. View at Publisher · View at Google Scholar · View at MathSciNet
  8. D. Needell and J. A. Tropp, “CoSaMP: iterative signal recovery from incomplete and inaccurate samples,” Applied and Computational Harmonic Analysis, vol. 26, no. 3, pp. 301–321, 2009. View at Publisher · View at Google Scholar · View at Zentralblatt MATH · View at MathSciNet
  9. H. Huang and A. Makur, “Backtracking-based matching pursuit method for sparse signal reconstruction,” IEEE Signal Processing Letters, vol. 18, no. 7, pp. 391–394, 2011. View at Publisher · View at Google Scholar · View at Scopus
  10. J. Capon, “High resolution frequency-wave number spectrum analysis,” Proceedings of the IEEE, vol. 57, no. 8, pp. 1408–1418, 1969. View at Google Scholar · View at Scopus
  11. J. Li and P. Stoica, “An adaptive filtering approach to spectral estimation and SAR imaging,” IEEE Transactions on Signal Processing, vol. 44, no. 6, pp. 1469–1484, 1996. View at Google Scholar · View at Scopus
  12. E. J. Kelly, “An adaptive detection algorithm,” IEEE Transactions on Aerospace and Electronic Systems, vol. 22, no. 2, pp. 115–127, 1986. View at Google Scholar · View at Scopus
  13. SparseLab, http://dsp.rice.edu/cs.
  14. A. C. Gürbüz, J. H. McClellan, and V. Cevher, “A compressive beamforming method,” in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '08), pp. 2617–2620, Las Vegas, Nev, USA, April 2008. View at Publisher · View at Google Scholar · View at Scopus
  15. I. Stojanovic, W. C. Karl, and M. Cetin, “Compressed sensing of mono-static and multi-static SAR,” in Algorithms for Synthetic Aperture Radar Imagery XVI, Proceedings of SPIE, Orlando, Fla, USA, April 2009. View at Publisher · View at Google Scholar · View at Scopus
  16. J. H. G. Ender, “On compressive sensing applied to radar,” Signal Processing, vol. 90, no. 5, pp. 1402–1414, 2010. View at Publisher · View at Google Scholar · View at Scopus
  17. Y. Yu, A. P. Petropulu, and H. V. Poor, “Measurement matrix design for compressive sensing-based MIMO radar,” IEEE Transactions on Signal Processing, vol. 59, no. 11, pp. 5338–5352, 2011. View at Publisher · View at Google Scholar · View at MathSciNet
  18. J. Zhang, D. Zhu, and G. Zhang, “Adaptive compressed sensing radar oriented toward cognitive detection in dynamic sparse target scene,” IEEE Transactions on Signal Processing, vol. 60, no. 4, pp. 1718–1729, 2012. View at Publisher · View at Google Scholar · View at MathSciNet
  19. Y. Chi, L. L. Scharf, A. Pezeshki, and A. R. Calderbank, “Sensitivity to basis mismatch in compressed sensing,” IEEE Transactions on Signal Processing, vol. 59, no. 5, pp. 2182–2195, 2011. View at Publisher · View at Google Scholar · View at MathSciNet
  20. Y. Bar-Shalom and T. E. Fortmann, Tracking and Data Association, Academic Press, Orlando, Fla, USA, 1988. View at MathSciNet