Methods and Gaussian criterion for statistical linearization of stochastic parametrically and externally excited nonlinear systems

The methods of Gaussian linearization along with a new Gaussian criterion used in the prediction of the stationary output variances of stable nonlinear oscillator subjected to both stochastic parametric and external excitations are presented. The techniques of Gaussian linearization are first derived and the accuracy in the prediction of the stationary output variances is illustrated. The justification of using Gaussian linearization a priori is further investigated by establishing a Gaussian criterion. The non-Gaussian effects due to system nonlinearities and/or large noise intensities in a Duffing oscillator are also illustrated. The validity of employing the Gaussian criterion test for assuring accuracy of Gaussian linearization is supported by performing the chi-square Gaussian goodness-of-fit test.