Self-Convolution and Its Invariant Properties for the Kernel Function of the Aortic Fractal Operator
In this paper, we explore the self-convolution of the kernel function of the aortic fractal operator. Previous research has established a model named “physical fractal”, and confirmed that the hemodynamics of the aorta can be inscribed by a fractal operator and that the dominant component of the kernel function of the fractal operator is a weighted first-order Bessel function. These studies primarily focus on solving the fractal operator kernel function and examining the overall properties of the physical fractal. As we began to investigate the internal structure of physical fractals, we discovered that studying the powers of fractal operators is a necessary step. In this paper, we introduce the concept of kernel function self-convolution, establish its connection with the power of the fractal operator, and derive a series of invariant properties for the self-convolution of the aortic operator kernel function. These invariant properties, in turn, are deeply and intrinsically related to the invariant properties of the Bessel functions. The research findings of this paper enrich hemodynamics and biomechanics in physical fractal space and extend the scope of using fractal operators to characterize the dynamics of living organisms.
Authors
- Gang Peng (ORCID: https://orcid.org/0000-0002-7925-1771)
- Dongan Li
- Yajun Yin (ORCID: https://orcid.org/0000-0002-7240-0922)
- Tianyi Zhou (ORCID: https://orcid.org/0009-0002-1721-6740)
- Chaoqian Luo (ORCID: https://orcid.org/0009-0000-2370-157X)
- Xiaobin Yu (ORCID: https://orcid.org/0000-0001-9716-0585)
Institutions
- University Town of Shenzhen (CN)
- Chengdu Technological University
- Qingdao University of Technology (CN)
- Tsinghua University (CN)
Publication Details
- Journal
- Fractal and Fractional
- Published
- 2024-12-11
- DOI
- https://doi.org/10.3390/fractalfract8120726
- Citations
- 1
- Primary Topic
- Complex Systems and Time Series Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.13
Funders
- National Natural Science Foundation of China