High order statistics used in identification of non-Gaussian processes by means of linear prediction models
DOI:
https://doi.org/10.3103/S073527270607003XAbstract
The paper proposes methods of using high order statistics for obtaining attributes in the problem of identification of non-Gaussian processes. Application of a set of generalized lattice filters, whose parameters are calculated from moment functions of the third and fourth orders, is shown to raise the probability of correct identification.References
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