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Rapid Generation of Stochastic Signals with Specified Statistics
We demonstrate a novel algorithm for generating stationary stochastic signals with a specified power spectral density (or equivalently, via the Wiener-Khinchin relation, a specified autocorrelation function) while satisfying constraints on the signal's probability density function.
Extended Koopman Models
We introduce two novel generalizations of the Koopman operator method of nonlinear dynamic modeling.
Coarse-Grained Nonlinear System Identification
We also demonstrate this approach experimentally, showing that it identifies an accurate model of the nonlinear voltage to luminosity dynamics of a tungsten filament with less than a second of experimental data.
