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The purpose of this paper is to adapt the empirical characteristic function (ECF) method to stable, but possibly not inverse stable linear stochastic system driven by the increments of a Lévy-process. A remarkable property of the ECF method for i.i.d. data is that, under an ideal setting, it gives an efficient estimate of the unknown parameters of a given parametric family of distributions. Variants...
The structured singular value μ has been widely studied for uncertain dynamical systems. Recently a great attention is paid to the probabilistic μ problem. Instead of computing the conservative worst-case μ we are interested in the probabilistic distribution of μ; given a probability distribution on the set of uncertainties. Traditionally this problem is solved by Monte Carlo algorithms. In this paper...
We study the problem of identifying a finite dimensional linear stochastic SISO system driven by a Lévy process. The latter are widely used in modelling financial time series. In a number of important examples the density function of the innovation term is unknown, but its characteristic function is explicitly known, possibly up to a few unknown parameters. In this paper we present and analyze a novel...
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