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Acoustics, Speech, and Signal Processing, IEEE International Conference on (1995)
Detroit, MI, USA
May 9, 1995 to May 12, 1995
ISBN: 0-7803-2431-5
pp: 3367-3369
Weibo Liang , Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
M.T. Manry , Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
Qiang Yu , Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
M.S. Dawson , Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
A.K. Fung , Dept. of Electr. Eng., Texas Univ., Arlington, TX, USA
ABSTRACT
In minimum mean square estimation, an estimate /spl theta/' of the random parameter vector /spl theta/ is obtained from an input vector y. We develop bounds on the variances of elements of /spl theta/'-/spl theta/ for the case where input signal vector y and the parameter vector /spl theta/ are non-Gaussian. First, we use linear transformations to obtain a new parameter vector /spl phi/ from /spl theta/ and a new input vector x from y. These new vectors are approximately Gaussian because of the central limit theorem, so stochastic Cramer-Rao bounds on the variance of /spl phi/'-/spl phi/ are tight. Lastly, bounds on variances of elements of /spl theta/-/spl theta/ are obtained.
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CITATION

W. Liang, M. Manry, M. Dawson, Q. Yu and A. Fung, "Stochastic Cramer Rao bounds for non-Gaussian signals and parameters," Acoustics, Speech, and Signal Processing, IEEE International Conference on(ICASSP), Detroit, MI, USA, 1995, pp. 3367-3369.
doi:10.1109/ICASSP.1995.479707
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