On the Construction and Analysis of a Fractional-Order Dirac Delta Distribution with Application

We introduce the generalized fractional-order Dirac delta distribution δGFODDF, defined by applying the generalized fractional derivative (GFD) operator to the Heaviside function. This construction extends the classical Dirac delta to non-integer orders, allowing modeling of systems with memory and non-local effects. We establish fundamental properties—including shifting, scaling, evenness, derivative, and convolution—within a rigorous distributional framework and present explicit proofs. Applications are demonstrated by solving linear fractional differential equations and by modeling drug release with fractional kinetics, where the new delta captures impulse responses with long-term memory. Numerical illustrations confirm that δGFODDF reduces to the classical delta when η=1, while providing additional flexibility for 0<η<1. These results show that δGFODDF is a powerful tool for fractional-order analysis in mathematics, physics, and biomedical engineering.

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Publication Details

Journal
Axioms
Published
2025-09-26
DOI
https://doi.org/10.3390/axioms14100728
Primary Topic
Fractional Differential Equations Solutions
Type
article
Field-Weighted Citation Impact
0.00

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article

On the Construction and Analysis of a Fractional-Order Dirac Delta Distribution with Application

Malik Sajjad Mehmood, Adil Jhangeer, Muhammad Muddassar, Liaqat Ali Khan et al.
Axioms
Fractional Differential Equations Solutions
article

On the Construction and Analysis of a Fractional-Order Dirac Delta Distribution with Application

Malik Sajjad Mehmood, Adil Jhangeer, Muhammad Muddassar, Liaqat Ali Khan, Nasir Siddiqui, Tahira Jabeen
article en

Abstract

We introduce the generalized fractional-order Dirac delta distribution δGFODDF, defined by applying the generalized fractional derivative (GFD) operator to the Heaviside function. This construction extends the classical Dirac delta to non-integer orders, allowing modeling of systems with memory and non-local effects. We establish fundamental properties—including shifting, scaling, evenness, derivative, and convolution—within a rigorous distributional framework and present explicit proofs. Applications are demonstrated by solving linear fractional differential equations and by modeling drug release with fractional kinetics, where the new delta captures impulse responses with long-term memory. Numerical illustrations confirm that δGFODDF reduces to the classical delta when η=1, while providing additional flexibility for 0<η<1. These results show that δGFODDF is a powerful tool for fractional-order analysis in mathematics, physics, and biomedical engineering.

AxiomsVol. 14(10)
Khazar University (AZ), International Islamic University, Islamabad (PK), VSB - Technical University of Ostrava (CZ), University of Engineering and Technology Taxila (PK)
European Commission
Openalex Percentile: Top 70%
Fractional Differential Equations Solutions
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