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Mittag-Leffler vector random fields with Mittag-Leffler direct and cross covariance functions

Annals of the Institute of Statistical Mathematics, 2013
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The Mittag-leffler and related functions

Integral Transforms and Special Functions, 1993
In our attempts to find solutions of fractional differential equations we are led, in a natural fashion, to the study of certain transcendental functions. These functions may be defined by a fractional integral or combinations of such integrals. Further investigations show that these new functions are intimately related to the classical Mittag-Leffler ...
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The Two-Parametric Mittag-Leffler Function

2014
In this chapter we present the basic properties of the two-parametric Mittag-Leffler function E α, β (z) (see ( 1.0.3)), which is the most straightforward generalization of the classical Mittag-Leffler function E α (z) (see ( 3.1.1)).
Rudolf Gorenflo   +3 more
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Mittag-Leffler Functions with Three Parameters

2014
The Prabhakar generalized Mittag-Leffler function [Pra71] is defined as $$\displaystyle{ E_{\alpha,\beta }^{\gamma }(z):=\sum _{ n=0}^{\infty } \frac{(\gamma )_{n}} {n!\varGamma (\alpha n+\beta )}\,z^{n}\,,\quad Re\,(\alpha ) > 0,\,Re\,(\beta ) > 0,\,\gamma > 0, }$$ (5.1.1) where (γ) n = γ(γ + 1)…(γ + n − 1) (see formula (A.1.17)).
Rudolf Gorenflo   +3 more
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Geometric Properties of Mittag-Leffler Functions

2018
In recent decades the attention towards Mittag-Leffler type functions has deepened due to their direct involvement in problems of physics, biology, chemistry, engineering and other applied sciences. More precisely, applications of Mittag-Leffler functions appear in stochastic systems (Polito and Scalas (2016)), statistical distribution with results ...
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Mittag–Leffler Synchronization of Delayed Fractional Memristor Neural Networks via Adaptive Control

IEEE Transactions on Neural Networks and Learning Systems, 2021
Yong-Gui Kao, Ying Li, Ju H. Park
exaly  

Global Mittag–Leffler Stability of the Delayed Fractional-Coupled Reaction-Diffusion System on Networks Without Strong Connectedness

IEEE Transactions on Neural Networks and Learning Systems, 2022
Yong-Gui Kao, Ju H. Park, Haibo Bao
exaly  

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