Generating Sparse Stochastic Processes Using Matched Splines
L. Dadi, S. Aziznejad, M. Unser
IEEE Transactions on Signal Processing, vol. 68, pp. 4397–4406, July 24, 2020.
We provide an algorithm to generate trajectories of sparse stochastic processes that are solutions of linear ordinary differential equations driven by Lévy white noises. A recent paper showed that these processes are limits in law of generalized compound-Poisson processes. Based on this result, we derive an off-the-grid algorithm that generates arbitrarily close approximations of the target process. Our method relies on a B-spline representation of generalized compound-Poisson processes. We illustrate numerically the validity of our approach.
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AUTHOR="Dadi, L. and Aziznejad, S. and Unser, M.",
TITLE="Generating Sparse Stochastic Processes Using Matched Splines",
JOURNAL="{IEEE} Transactions on Signal Processing",
YEAR="2020",
volume="68",
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pages="4397--4406",
month="July 24,",
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