A simple algorithm for generating spectrally colored, non-Gaussian signals

• Published in: Probabilistic engineering mechanics Vol. 25; no. 3; pp. 315 - 322
• Main Authors: Nichols, J.M., Olson, C.C., Michalowicz, J.V., Bucholtz, F.
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.07.2010; Elsevier
• Subjects: Algorithms; Colored noise; Computer simulation; Density; Exact sciences and technology; Fundamental areas of phenomenology (including applications); Gaussian; Non-Gaussian; Physics; Probability density functions; Random process; Random processes; Solid mechanics; Spectra; Structural and continuum mechanics; Surrogate data; Transformations; Vibration, mechanical wave, dynamic stability (aeroelasticity, vibration control...); Non-Gaussian; Random process; Surrogate data; Colored noise; Non gaussian noise; Spectral energy distribution; Power spectral density; Iterative method; Color noise; Stochastic process; Non linear transformation; Gaussian process; Gaussian processes; Probability density function; Stationary process; Spectral density
• ISSN: 0266-8920; 1878-4275
• DOI: 10.1016/j.probengmech.2010.01.005

This work describes a simple method for generating signals conforming to a stationary random process for which the practitioner specifies both the power spectral density function and the marginal probability density function. The general approach is to first create a Gaussian random process with the appropriate spectral density and then apply a memoryless nonlinear transformation to achieve the desired marginal density. The transformation is not specified a priori but rather is simulated via an iterative “shuffling” procedure. The method is very simple to implement and yields results that are comparable to some of the more complicated methods.