IMAL 13325
INSTITUTO DE MATEMATICA APLICADA DEL LITORAL "DRA. ELEONOR HARBOURE"
Unidad Ejecutora - UE
artículos
Título:
Heavy tailed approximate identities and sigma-stable Markov kernels
Autor/es:
AIMAR HUGO; MORANA, FEDERICO; GÓMEZ IVANA
Revista:
POTENTIAL ANALYSIS
Editorial:
SPRINGER
Referencias:
Lugar: Berlin; Año: 2018 vol. 48 p. 473 - 493
ISSN:
0926-2601
Resumen:
The aim of this paper is to present some results relating the properties of stability, concentration and approximation to the identity of convolution through non-necessarily mollification type families of heavy tailed Markov kernels. A particular case is provided by the kernels $K_t$ obtained as the $t$ mollification of $L^{\sigma(t)}$ selected from the family $\mathcal{L}=\{L^{\sigma}: \widehat{L^{\sigma}}(\xi)=e^{-\abs{\xi}^\sigma}, 0
