A method is outlined for calculating the .expected number of maxima or minima of a random process with non-Gaussian frequency distribution from the statistical moments of the process and its first two derivatives. This method is based on an estimate of the joint frequency function of the process and its first two derivativesgiven by means of a generalized form of Edgeworth’s series; the procedure thus consists essentially in applying a correction to the results for a Gaussian process. The func?tions required in this procedure are calculated for the first two correc-tion terms; therefore, the effects of skewness and kurtosis can be cal?culated, provided the required moments are known. Expressions are given for these moments in terms of multiple, correlation functions and multi-spectra, and the relations between these functions for a random output of a linear system arid those for the random input are indicated.
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