Advertisement

Detection of Known Signals in Gaussian Noise

  • Bernard C. Levy
Chapter

Keywords

Gaussian Noise Detection Problem Colored Noise Optimum Detector Distorted Signal 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    D. O. North, “An analysis of the factors which determine signal/noise discrimination in pulse-carrier systems,” Tech. Rep. PTR-6C, RCA Laboratory, June 1943. Reprinted in Proc. IEEE, vol. 51, pp. 1016–1027, July 1963.Google Scholar
  2. 2.
    J. H. Van Vleck and D. Middleton, “A theoretical comparison of the visual, aural and meter reception of pulsed signals in the presence of noise,” J. Applied Phys., vol. 17, pp. 940–971, 1946. Originally published in May 1944 as a classified Harvard Radio Research Lab. technical report.CrossRefGoogle Scholar
  3. 3.
    J. G. Proakis, Digital Communications, Fourth Edition. New York: McGraw-Hill, 2000.Google Scholar
  4. 4.
    H. Hochstadt, Integral Equations. New York: Wiley-Interscience, 1989. Reprint edition.MATHGoogle Scholar
  5. 5.
    B. C. Levy, R. Frezza, and A. J. Krener, “Modeling and estimation of discrete-time Gaussian reciprocal processes,” IEEE Trans. Automatic Control, vol. 35, pp. 1013–1023, Sept. 1990.CrossRefMATHMathSciNetGoogle Scholar
  6. 6.
    M. H. Hayes, Statistical Digital Signal Processing and Modeling. New York: J. Wiley & Sons, 1996.Google Scholar
  7. 7.
    A. J. Laub, Matrix Analysis for Scientists and Engineers. Philadelphia, PA: Soc. for Industrial and Applied Math., 2005.CrossRefMATHGoogle Scholar
  8. 8.
    T. Kailath, A. H. Sayed, and B. Hassibi, Linear Estimation. Upper Saddle River, NJ: Prentice Hall, 2000.Google Scholar
  9. 9.
    J. R. Gabriel and S. M. Kay, “On the relationship between the GLRT and UMPI tests for the detection of signals with unknown parameters,” IEEE Trans. Signal Proc., vol. 53, pp. 4194–4203, Nov. 2005.Google Scholar
  10. 10.
    I. C. Gohberg and M. G. Krein, Theory and Applications of Volterra Operators in Hilbert Space, vol. 24 of Trans. of Mathematical Monographs. Providence, RI: Amer. Math. Society, 1970.Google Scholar
  11. 11.
    H. L. Van Trees, Detection, Estimation and Modulation Theory, Part I: Detection, Estimation and Linear Modulation Theory. New York: J. Wiley & Sons, 1968. Paperback reprint edition in 2001.Google Scholar
  12. 12.
    R. N. McDonough and A. D. Whalen, Detection of Signals in Noise, Second Edition. San Diego, CA: Academic Press, 1995.Google Scholar
  13. 13.
    C. W. Helstrom, Elements of Signal Detection & Estimation. Upper Saddle River, NJ: Prentice-Hall, 1995.MATHGoogle Scholar
  14. 14.
    H. V. Poor, An Introduction to Signal Detection and Estimation, Second Edition. New York: Springer Verlag, 1994.Google Scholar
  15. 15.
    T. Kailath, “RKHS approach to detection and estimation problems–part i: Deterministic signals in Gaussian noise,” IEEE Trans. Informat. Theory, vol. 17, pp. 530–549, 1971.CrossRefMATHMathSciNetGoogle Scholar
  16. 16.
    T. Kailath and H. V. Poor, “Detection of stochastic processes,” IEEE Trans. Informat. Theory, vol. 44, pp. 2230–2259, Oct. 1998.CrossRefMATHMathSciNetGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  • Bernard C. Levy
    • 1
  1. 1.University of CaliforniaDavisUSA

Personalised recommendations