Abstract
Given an arbitrary power spectrum S X (f) or, equivalently, its inverse Fourier transform, the autocovariance function γx(τ), our ability to simulate the corresponding stationary random signals X(t), using only the pseudo-random number generator, which produces, say, discrete-time white noise, depends on the observation that, in some sense, all stationary random signals can be approximated by superpositions of random harmonic oscillations such as those discussed in Examples 4.1.2 and 4.1.9.
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© 2011 Springer Science+Business Media, LLC
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Woyczyński, W.A. (2011). Spectral Representation of Discrete-Time Stationary Signals and Their Computer Simulations. In: A First Course in Statistics for Signal Analysis. Birkhäuser Boston. https://doi.org/10.1007/978-0-8176-8101-2_9
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DOI: https://doi.org/10.1007/978-0-8176-8101-2_9
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