Asymptotically optimal detection in incompletely characterized non-Gaussian noise

  title={Asymptotically optimal detection in incompletely characterized non-Gaussian noise},
  author={Steven M. Kay},
  journal={IEEE Trans. Acoustics, Speech, and Signal Processing},
The problem of detecting a signal known except for amplitude in non-Gaussian noise is addressed. The noise samples are assumed to be independent and identically distributed with a probability density function known except for a few parameters. Using a generalized likelihood ratio test, it is proven that for a symmetric noise probability density function, the detection performance is asymptotically equivalent to that obtained for a detector designed with a priori knowledge of the noise… CONTINUE READING
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Asymptotically optimal detection in unknown colored noise via autoregressive modeling,

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