Sets of fractional operators and numerical estimation of the order of convergence of a family of fractional fixed-point methods

Torres Hernandez, Anthony; Brambila Paz, Fernando

doi:http://dx.doi.org/10.3390/fractalfract5040240

Sets of fractional operators and numerical estimation of the order of convergence of a family of fractional fixed-point methods

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Torres Hernandez A, Brambila Paz F. Sets of fractional operators and numerical estimation of the order of convergence of a family of fractional fixed-point methods. Fractal Fract. 2021;5(4):240. DOI: 10.3390/fractalfract5040240

Abstract

Considering the large number of fractional operators that exist, and since it does not seem that their number will stop increasing soon at the time of writing this paper, it is presented for the first time, as far as the authors know, a simple and compact method to work the fractional calculus through the classification of fractional operators using sets. This new method of working with fractional operators, which may be called fractional calculus of sets, allows generalizing objects of conventional calculus, such as tensor operators, the Taylor series of a vector-valued function, and the fixed-point method, in several variables, which allows generating the method known as the fractional fixed-point method. Furthermore, it is also shown that each fractional fixed-point method that generates a convergent sequence has the ability to generate an uncountable family of fractional fixed-point methods that generate convergent sequences. So, it is presented a method to estimate numerically in a region W the mean order of convergence of any fractional fixed-point method, and it is shown how to construct a hybrid fractional iterative method to determine the critical points of a scalar function. Finally, considering that the proposed method to classify fractional operators through sets allows generalizing the existing results of the fractional calculus, some examples are shown of how to define families of fractional operators that satisfy some property to ensure the validity of the results to be generalized.