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Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
ISSN: 1058-6393
ISBN: 0-8186-6405-3
pp: 283-287
S.D. Gordon , Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA
J.A. Ritcey , Dept. of Electr. Eng., Washington Univ., Seattle, WA, USA
ABSTRACT
We present a new approach to the modeling of non-Gaussian complex random signals. The method transforms an underlying complex white Gaussian sequence, whose magnitude is shaped by a zero memory non-linear (ZMNL) transformation. In this way, we match the magnitude PDF, and the power spectral density of the non-Gaussian output. The ZMNL technique has the additional benefits of synthesizing complex, positive, or real valued signals by keeping only portions of the complex signal. This provides a quick simulation capability. The JPDF of a multivariate sample is easily computed from our model. We use this to form a likelihood detector for the presence of our non-Gaussian versus a white Gaussian signal. The dramatic improvement of the likelihood detector compared with a Gaussian based quadratic detector is presented.<>
INDEX TERMS
random processes, maximum likelihood detection, probability, transforms, covariance matrices, signal synthesis, Gaussian processes, spectral analysis
CITATION

S. Gordon and J. Ritcey, "A transformation approach for modeling and detecting non-Gaussian signals," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 283-287.
doi:10.1109/ACSSC.1994.471461
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