High order statistics used in identification of non-Gaussian processes by means of linear prediction models

Authors

DOI:

https://doi.org/10.3103/S073527270607003X

Abstract

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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Published

2006-07-03

Issue

Vol. 49 No. 7 (2006)

Section

Research Articles