Multidimensional probability density function approximations for detection, classification, and model order selection

@article{Kay2001MultidimensionalPD,
  title={Multidimensional probability density function approximations for detection, classification, and model order selection},
  author={Steven M. Kay and Albert H. Nuttall and Paul M. Baggenstoss},
  journal={IEEE Trans. Signal Processing},
  year={2001},
  volume={49},
  pages={2240-2252}
}
This paper addresses the problem of calculating the multidimensional probability density functions (PDFs) of statistics derived from known many-to-one transformations of independent random variables (RVs) with known distributions. The statistics covered in the paper include reflection coefficients, autocorrelation estimates, cepstral coefficients, and general linear functions of independent RVs. Through PDF transformation, these results Can be used for general PDF approximation, detection… CONTINUE READING

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