p-Adic Cellular Neural Networks With Delay

Author

Baboucarr Dibba, The University of Texas Rio Grande Valley

Date of Award

7-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Mathematics

First Advisor

Wilson Zuniga-Galindo

Second Advisor

Sergey Grigorian

Third Advisor

Vesselin Vatchev

Abstract

This dissertation presents a novel framework for p-adic reaction-diffusion cellular neural networks (CNNs) with delay, offering new insights into the stability and dynamic behavior of these networks. Through numerical simulations, we explore their response to various conditions, highlighting their capability to model complex systems. Additionally, this work reviews cutting-edge developments in p-adic CNNs, particularly their application to advanced image processing tasks such as edge detection and noise filtering, demonstrating their effectiveness in preserving critical image features while filtering out noise. This dissertation is written in collaboration with my Ph.D supervisor and Dr. Zambrano-Luna, Brian.

Comments

Copyright 2025 Baboucarr Dibba. All Rights Reserved.

https://proquest.com/docview/3246996675

Recommended Citation

Baboucarr, D. (2025). p-Adic Cellular Neural Networks With Delay [Doctoral dissertation, The University of Texas Rio Grande Valley]. ScholarWorks @ UTRGV. https://scholarworks.utrgv.edu/etd/1735