Digital spectral analysis: with applications
Digital spectral analysis: with applications
Parametric identification of linear systems using Laplace transform
Automation and Remote Control
Symmetric Laplace transform and its application to parametric identification of linear systems
Automation and Remote Control
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The Laplace image of stationary random normal processes is studied. The covariance function of the Laplace image of white noise is converted by a linear shaping filter into the covariance function of the Laplace image of the filter output process. The relationship between the covariance function of the Laplace image of a random process and the autocovariance function and spectral density is determined. The covariance function of the Laplace image of measurement errors of a transition process in a stationary linear system is applied in optimal nonparametric identification of the transfer function.