Share This Article:

Parametrically Optimal, Robust and Tree-Search Detection of Sparse Signals

Full-Text HTML XML Download Download as PDF (Size:236KB) PP. 336-342
DOI: 10.4236/jsip.2013.43042    2,120 Downloads   3,024 Views   Citations

ABSTRACT

We consider sparse signals embedded in additive white noise. We study parametrically optimal as well as tree-search sub-optimal signal detection policies. As a special case, we consider a constant signal and Gaussian noise, with and without data outliers present. In the presence of outliers, we study outlier resistant robust detection techniques. We compare the studied policies in terms of error performance, complexity and resistance to outliers.

Conflicts of Interest

The authors declare no conflicts of interest.

Cite this paper

A. Burrell and P. Papantoni-Kazakos, "Parametrically Optimal, Robust and Tree-Search Detection of Sparse Signals," Journal of Signal and Information Processing, Vol. 4 No. 3, 2013, pp. 336-342. doi: 10.4236/jsip.2013.43042.

References

[1] E. J. Candes, J. Romberg and T. Tao, “Robust Uncertainty Principles: Exact Signal Reconstruction from Highly Incomplete Frequency Information,” IEEE Transactions on Information Theory, Vol. 52, No. 2, 2006, pp. 489-509. doi:10.1109/TIT.2005.862083
[2] J. A. Tropp and A. C. Gilbert, “Signal Recovery from Random Measurements via Orthogonal Matching Pursuit,” IEEE Transactions on Information Theory, Vol. 53, No. 2, 2007, pp. 4655-4666. doi:10.1109/TIT.2007.909108
[3] J. F. Hayes, “An Adaptive Technique for Local Distribution,” IEEE Transactions on Communications, Vol. 26, No. 8, 1978, pp. 1178-1186. doi:10.1109/TCOM.1978.1094204
[4] J. I. Capetanakis, “Tree Algorithms for Packet Broadcast Channels,” IEEE Transactions on Information Theory, Vol. 25, No. 5, 1979, pp. 505-515. doi:10.1109/TIT.1979.1056093
[5] A. T. Burrell and P. Papantoni-Kazakos, “Random Access Algorithms in Packet Networks: A Review of Three Research Decades,” International Journal of Communications Network and System Sciences (IJCNS), Vol. 5, No. 10, 2012, pp. 691-707. doi:10.4236/ijcns.2012.510072
[6] P. Huber, “A Robust Version of the Probability Ratio Test,” The Annals of Mathematical Statistics, Vol. 36, 1965, pp. 1753-1758. doi:10.1214/aoms/1177699803
[7] D. Kazakos and P. Papantoni-Kazakos, “Detection and Estimation,” Computer Science Press, 1990.
[8] A. T. Burrell and P. Papantoni-Kazakos, “Extended Sequential Algorithms for Detecting Changes in Acting Stochastic Processes,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 28, No. 5, 1998, pp. 703-710. doi:10.1109/3468.709621
[9] A. T. Burrell and P. Papantoni-Kazakos, “Robust Sequential Algorithms for the Detection of Changes in Data Generating Processes,” Journal of Intelligent and Robotic Systems, Vol. 60, No. 1, 2010, pp. 3-17.

  
comments powered by Disqus

Copyright © 2018 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.