Linear Canonical Transform Approach to the Characteristic Function of Real Random Variables

The present research demonstrates the utility of the linear canonical transform (LCT) in constructing the characteristic function of real random variables. We refer to this construction as the linear canonical characteristic function (LCCF). The proposed LCCF aims to address the limitations of the classical characteristic function in both theoretical and applied aspects. Using this approach, we investigate its properties, such as Hermitian symmetry, continuity, convolution, and derivatives, which are generalized forms of the classical characteristic function in the literature. Finally, we implement the obtained results by calculating several probability density functions in the LCCF domains.

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Publication Details

Journal
Eng—Advances in Engineering
Published
2026-01-04
DOI
https://doi.org/10.3390/eng7010026
Primary Topic
Statistical Mechanics and Entropy
Type
article
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article

Linear Canonical Transform Approach to the Characteristic Function of Real Random Variables

Mawardi Bahri, syamsuddin Toaha, Nasrullah Bachtiar, Andi Tenri Ajeng Nur et al.
Eng—Advances in Engineering
Statistical Mechanics and Entropy
article

Linear Canonical Transform Approach to the Characteristic Function of Real Random Variables

Mawardi Bahri, syamsuddin Toaha, Nasrullah Bachtiar, Andi Tenri Ajeng Nur, Risnawati Ibnas
article en

Abstract

The present research demonstrates the utility of the linear canonical transform (LCT) in constructing the characteristic function of real random variables. We refer to this construction as the linear canonical characteristic function (LCCF). The proposed LCCF aims to address the limitations of the classical characteristic function in both theoretical and applied aspects. Using this approach, we investigate its properties, such as Hermitian symmetry, continuity, convolution, and derivatives, which are generalized forms of the classical characteristic function in the literature. Finally, we implement the obtained results by calculating several probability density functions in the LCCF domains.

Eng—Advances in EngineeringVol. 7(1)
Sriwijaya University (ID), Sumatera Institute of Technology (ID), Hasanuddin University (ID)
Reduced inequalities
Openalex Percentile: Top 96%
Statistical Mechanics and Entropy
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