VILLA , Silvia

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We derive strongly convergent algorithms to solve inverse problems involving elastic-net regularization. Moreover, using functional analysis techniques we provide a rigorous study of the asymptotic properties of the regularized solutions that allows to cast in a unified framework l^1, elastic-net and classical Tikhonov regularization.

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Nanoparticles have come and continue to be an extremely interesting research topic due to the variety of applications, deriving from the possibility to opportunely tailor their properties through different preparation methods. Among nanoparticles, magnetic nanostructures, due to their special characteristics, represent an interesting tool for...

We extend the classical Mercer theorem to reproducing kernel Hilbert spaces whose elements are functions from a measurable space X into Cn. Given a finite measure μ on X, we represent the reproducing kernel K as a convergent series in terms of the eigenfunctions of a suitable compact operator depending on K and μ. Our result holds under the...