Two algorithms of sampling reconstruction procedures of non Gaussian processes are investigated. The optimalalgorithm is analyzed on the basis of the conditional mean rule and cumulant functions. In this case the err...
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ISBN:
(纸本)9781618040053
Two algorithms of sampling reconstruction procedures of non Gaussian processes are investigated. The optimalalgorithm is analyzed on the basis of the conditional mean rule and cumulant functions. In this case the error reconstruction function depends on the given samples and on the probability density function of the given process. The non optimal algorithm is only based on the covariance function of the output process. We investigate the non Gaussian processes on the output of exponential and polynomial converters driven by the Gaussian Markov process. Comparison of both algorithms is given.
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