Estimating Random Integrals from Noisy Observations: Sampling Designs and Their Performance.
Technical rept. Sep 84-Aug 85,
NORTH CAROLINA UNIV AT CHAPEL HILL CENTER FOR STOCHASTIC PROCESSES
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The problem of estimating a weighted average of a random process from noisy observations at a finite number of sampling points is considered. The performance of sampling designs with optimal or suboptimal, but easily computable, estimator coefficients is studied. Several examples and special cases are studied included additive independent noise, nonlinear distortion with noise, and quantization noise. Author
- Statistics and Probability