Special Session 4: Delay and Functional Differential Equations and Applications

Delay on time of Fractional Diabetes Model with Optimal Control, Numerical Treatments

Muner Abou Hasan
emirates aviation university
United Arab Emirates
Co-Author(s):    Muner M. Abou Hasan, Hannah Al Ali, Zindoga Mukandavire, Seham M. Al-Mekhlafi
Abstract:
In this paper, we presented the fractional optimal control of the diabetes disease mathematical model with time delay. The fractional order operator is defined in the Caputo sense. A control variable is considered to reduce the glucose in the blood by controlling insulin. The discretization of the nonstandard finite difference and Gr\{u}nwald$-$Letnikov is constructed to solve the obtained optimality system numerically. The stability analysis of the proposed method is studied. Numerical examples and comparative studies for testing the applicability of the utilized method and to show the simplicity of this approximation approach are presented.

Artificial Neural Networks for Stability Analysis and Simulation of Delayed Rabies Spread Models

Ateq Alsaadi
Taif university
Saudi Arabia
Co-Author(s):    Ramsha Shafqat
Abstract:
This article presents a delay differential equations model to track the spread of rabies among dog and human populations. It considers two delay effects on vaccination efficacy and incubation duration, and uses singular and non-singular kernels to evaluate other factors influencing rabies transmission. The model`s uniqueness is established using fixed point, piecewise derivative, and integral approaches. A piecewise numerical iteration scheme based on Newton interpolation polynomials is used to obtain an approximate solution. The study aims to improve our understanding of rabies spread dynamics using a novel piecewise derivative approach, clarifying the concept of piecewise derivatives and their significance in understanding crossover dynamics. The dataset is divided into training, testing, and validation sets using Artificial Neural Network (ANN) approaches.

Stochastic epidemic model based on Markovian switching with time delay

Hebatallah Alsakaji
UAE University
United Arab Emirates
Co-Author(s):    Fathalla Rihan
Abstract:
The dynamics of disease transmission are influenced by environmental changes. In this study, we incorporate unreported cases (U), environmental disturbances, and external events into the Susceptible; Exposed; Infectious; Unreported; Removed (SEIUR) epidemic model with time delays. We analyze the random transitions between different regimes. The criteria for ergodicity and stationary distribution are explored, and a Lyapunov function is employed to establish conditions under which the disease may be eradicated. Sudden external events, like hurricanes, can significantly impact disease spread during regime transitions. Numerical simulations are used to validate the model and the theoretical findings.

Non-Lipschitz Liapunov Functionals of Functional Differential Equations

Zhivko S. Athanassov
Bulgarian Academy of Sciences
Bulgaria
Co-Author(s):    
Abstract:
In this talk, we first present a new Liapunov theory for functional differential equations of the retarded type by using semicontinuous Liapunov functionals. We define a type of derivative for functionals which are assumed to be lower semicontinuous and prove a comparison theorem for this class of functionals. One of the fundamental problems in differential equations is the characterization of invariance of a set. In ordinary differential equations, it is known that invariance of a closed set is equivalent to a notion called subtangent. That theorem was first proved by Nagumo (1942) and was later rediscovered by many authors. We give a complete generalization of Nagumo theorem to functional differential equations. The new Liapunov theory developed is our main tool. An invariance principle for asymptotically autonomous systems is given as an application.

Delay equations in sequentially complete locally convex vector spaces

Christian Budde
University of the Free State
So Africa
Co-Author(s):    Christian Seifert
Abstract:
This work is initially motivated motivated by the work of B\`{a}tkai and Piazzera \cite{BP2005,BP2001}. They studied partial differential equations with finite delay using an operator theoretical approach by means of $C_0$-semigroups. The theory of strongly continuous one-parameter operator semigroups is well-developed. However, also this theory has its limitations as one deals with operators on a given Banach space. \medskip A possible generalization of the concept of $C_0$-semigroups on Banach spsaces are operator semigroups on locally convex spaces. There has been a lot of research regarding the formulation of operator semigroup theory on those spaces. The class of locally equicontinuous semigroups has been investigated for example by Dembard \cite{D1974}, Babalola \cite{Ba1974}, Ouchi \cite{O1973} and Komura \cite{Ko1968}. Here, one has to be a little bit more careful when it comes to resolvents as one only can work with so-called asymptotic resolvents as the Laplace transform does not need to converge. \medskip We show that one can combine equations with both finite and infinite delay in one theory. Evolution equations with infinite delay have been explored on their own by several authors not only on Banach spaces but also on Frechet spaces. However, it is worth mentioning, that Picard, Trostorff and Waurick showed \cite{PTW2014} that they do not need different treatment. \medskip This is joint work with C.~Seifert (Technical University Hamburg, Germany). \begin{thebibliography}{10} \bibitem{Ba1974} V.~A. Babalola. \newblock Semigroups of operators on locally convex spaces. \newblock {\em Trans. Am. Math. Soc.}, 199:163--179, 1974. \bibitem{BP2001} A.~B{\`a}tkai and S.~Piazzera. \newblock Semigroups and linear partial differential equations with delay. \newblock {\em J. Math. Anal. Appl.}, 264(1):1--20, 2001. \bibitem{BP2005} A.~B{\`a}tkai and S.~Piazzera. \newblock {\em Semigroups for delay equations}, volume~10 of {\em Res. Notes Math.} \newblock Wellesley, MA: A K Peters, 2005. \bibitem{D1974} B.~Dembart. \newblock On the theory of semigroups of operators on locally convex spaces. \newblock {\em J. Funct. Anal.}, 16:123--160, 1974. \bibitem{Ko1968} T.~Komura. \newblock Semigroups of operators in locally convex spaces. \newblock {\em J. Funct. Anal.}, 2:258--296, 1968. \bibitem{O1973} S.~Ouchi. \newblock Semi-groups of operators in locally convex spaces. \newblock {\em J. Math. Soc. Japan}, 25:265--276, 1973. \bibitem{PTW2014} R.~Picard, S.~Trostorff, and M.~Waurick. \newblock A functional analytic perspective to delay differential equations. \newblock {\em Oper. Matrices}, 8(1):217--236, 2014. \end{thebibliography}

Stability and Convergence in Asymptotic Systems of Neural Networks with Infinite Delays

Ahmed Elmwafy
Universidade da Beira Interior
Portugal
Co-Author(s):    A. Elmwafy, Jos\`{e} J. Oliveira, C\`esar M. Silva
Abstract:
We investigate both the global exponential stability and the existence of a periodic solution of a general differential equation with unbounded distributed delays. The main stability criterion depends on the dominance of the non-delay terms over the delay terms. The criterion for the existence of a periodic solution is obtained with the application of the coincidence degree theorem. We use the main results to get criteria for the existence and global exponential stability of periodic solutions of a generalized higher-order periodic Cohen-Grossberg neural network model with discrete-time varying delays and infinite distributed delays. Additionally, we provide a comparison with the results in the literature and a numerical simulation to illustrate the effectiveness of some of our results.

Refined Caputo Fractional Derivative for Non-Singular Nonlinear Systems with Delay: Its Application to Suppress the Aedes Aegypti Mosquitoes via Wolbachia

Soundararajan Ganesan
Nazarbayev University
Kazakhstan
Co-Author(s):    Gopalakrishnan Karnan; Ardak Kashkynbayev; Minvydas Ragulskis; Chien-Chang Yen
Abstract:
This study refines the Caputo fractional derivative for non-singular nonlinear functions, unifying Riemann-Liouville and Caputo derivatives. We introduce an improved fractional derivative operator to establish stability outcomes for a model addressing cytoplasmic incompatibility in \textit{Aedes Aegypti} mosquitoes. This work builds on existing research where the Caputo-Fabrizio operator was used in logistic growth equations, confirming solution existence, uniqueness, and $\alpha$-exponential stability. However, previous studies overlooked the non-singular aspects of nonlinear growth factors, which are crucial for our model. We extend existing results to a new fractional-order operator using singular and non-singular kernel functions and their well-posedness properties. Our mathematical model aims to increase cytoplasmic incompatibility in \textit{Aedes Aegypti} by releasing \textit{Wolbachia}-infected mosquitoes, reducing mosquito populations and the incidence of diseases like Dengue, Zika, Chikungunya, and Yellow Fever. We establish conditions for delay-dependent exponential stability using a Lyapunov-Kraskovskii functional and the linear matrix inequality framework. Finally, a numerical example with comparative analysis validates the theoretical outcomes of the improved fractional operator within the population model using real-world data.

On the qualitative behavior of a Hepatitis B epidemic model with a non-standard finite difference scheme

Mehmet Gumus
Zonguldak Bulent Ecevit University
Turkey
Co-Author(s):    Kemal Turk
Abstract:
Hepatitis B is a significant global health issue with serious consequences like liver cancer, cirrhosis, and liver failure. The virus spreads through contact with infected blood, body fluids, or contaminated needles. With over 350 million chronic carriers and about 800,000 deaths annually, primarily from liver cancer and cirrhosis, it remains a major global threat. Despite advanced preventive treatments, including effective vaccination programs, the risk of chronic Hepatitis B virus infection persists. The dynamics of the spread of the Hepatitis B virus can be modeled mathematically. Epidemiological models are often formulated as systems of non-linear differential equations. These models can be discretized using methods like Euler and Runge-Kutta, but these can lead to undesirable behaviors such as incorrect equilibrium points or numerical instabilities. To address these issues, a non-standard finite difference scheme can be constructed. In this study, a Hepatitis B virus model will be discussed, and a non-standard finite difference scheme for this system will be established. It will be shown that the discrete system provides dynamically consistent results with the continuous model, regardless of the time step size $h$, regarding the positivity and boundedness of solutions, equilibrium points, basic reproduction number, and stability behavior. Numerical simulations will support theoretical results.

Non-Markovian models of collective motion

Jan Haskovec
King Abdullah University of Science and Technology
Saudi Arabia
Co-Author(s):    
Abstract:
I will give an overview of recent results for models of collective behavior governed by functional differential equations with non-Markovian structure. The talk will focus on models of interacting agents with applications in biology (flocking, swarming), social sciences (opinion formation) and engineering (swarm robotics), where latency (delay) plays a significant role. I will characterize two main sources of delay - inter-agent communications (transmission delay) and information processing (reaction delay) - and discuss their impacts on the group dynamics. I will give an ovierview of analytical methods for studying the asymptotic behavior of the models in question and their mean-field limits. In particular, I will show that the transmission vs. reaction delay leads to fundamentally different mathematical structures and requires appropriate choice of analytical tools. Finally, motivated by situations where finite speed of information propagation is significant, I will introduce an interesting class of problems where the delay depends nontrivially and nonlinearly on the state of the system, and discuss the available analytical results and open problems here.

Numerov Method for a Weakly Coupled System of Singularly Perturbed Delay Differential Equations

Dany Joy
Vellore Institute of Technology, Vellore
India
Co-Author(s):    Dinesh Kumar S and Fathalla A Rihan
Abstract:
This article presents an efficient numerical method for solving a weakly coupled system of singularly perturbed delay differential equations. The technique involves approximating the first-order derivative in the system using a Taylor series, followed by applying the Numerov method. A scheme incorporating a fitting factor is developed to solve the problem. To evaluate the method`s accuracy, error estimation is performed using the maximum principle, and theoretical justifications are provided through relevant numerical examples with varying perturbation parameters and mesh sizes. The numerical results are expressed in terms of maximum absolute errors and the rate of convergence. Our approach is shown to be uniformly convergent to the first order, as demonstrated by the tabulated values. Compared to previously published methodologies, this approach yields improved results and makes a valuable contribution to the existing literature.

Asymptotic and exponential mean square stability of variable step size numerical solutions for stochastic pantograph differential equations

Udhayakumar Kandasamy
United Arab University
United Arab Emirates
Co-Author(s):    K. Udhayakumar, Fathalla A. Rihan
Abstract:
The mean square stability analysis of the numerical theta methods of stochastic models has gained significant interest. However, more research is needed about the mean square stability of stochastic pantograph differential equations (SPDEs). This work uses two different numerical theta methods to research the asymptotic and exponential mean square stability of numerical solutions for SPDEs. SPDEs are very special stochastic delay differential equations with unbounded memory. The problem of computer memory hold, when the numerical methods with constant step-size are applied to the SPDEs. Thus, we are interested in numerical theta methods with variable step-size for SPDEs. By using a coupled condition, the asymptotic mean square stability of the classical stochastic theta method with $\theta \geq 0.5$ and exponential mean square stability of the split-step theta method with $\theta > 0.5$ under variable step-size have been researched. Conditional stability results for the methods with $\theta < 0.5 $ are also obtained under a stronger assumption. Finally, some illustrative numerical examples are presented to show the efficiency of the methods.

Numerical approximation for singularly perturbed differential equations exhibiting significant positive shift arising in neuronal activity

Akhila Mariya Regal
Vellore Institute of Technology, Vellore
India
Co-Author(s):    Dinesh Kumar S
Abstract:
An approximation technique for singularly perturbed differential equations with a large positive shift parameter is presented in this article. The recommended numerical scheme is solved using the Gauss elimination method in MATLAB R2022a. The proposed scheme achieves a linear rate of convergence on a uniform grid. The convergence results, both theoretical and numerical, have been demonstrated and confirmed to be consistent with the proposed scheme. A few examples are provided in tables and charts to compute and demonstrate the theoretical analysis results. When compared to existing literature, our method produces better outcomes with lower error rates for the specified examples.

Finite-Time Synchronization of Complex-Valued Fractional Order Memristive Neural Networks with Time-Varying Delays

Madina Otkel
Nazarbayev University
Kazakhstan
Co-Author(s):    Ardak Kashkynbayev, Soundararajan Ganesan, Rakkiyappan Rajan
Abstract:
This paper investigates the problem of finite-time synchronization in complex-valued fractional-order memristive neural networks (CVMFONNs) with time-varying delays. The focus is on developing novel synchronization criteria and control strategies that ensure finite-time synchronization despite the inherent complexities introduced by fractional-order dynamics, memristive characteristics, and complex-valued states. By employing Lyapunov functional methods and fractional-order calculus, we derive sufficient conditions for finite-time synchronization, accounting for the influence of time-varying delays on system stability. The proposed control schemes are validated through rigorous theoretical analysis and numerical simulations, demonstrating their effectiveness and robustness. Our results contribute to the understanding and application of fractional-order neural networks in real-world scenarios where rapid synchronization is critical, offering potential insights for advancements in neuromorphic computing and complex system modeling.

DELAY DIFFERENTIAL EQUATIONS AND APPLICATIONS TO BIOLOGY

Fathalla Rihan
United Arab Emirates University
United Arab Emirates
Co-Author(s):    Fathalla A. Rihan
Abstract:
Recently much attention has been given to mathematical modeling of real-life phenomena using differential equations with memory, such as delay differential equations (DDEs). This is because introducing memory terms in a differential model significantly increases the complexity of the model. Such a class of DDEs is widely used for analysis and predictions in various areas of life sciences and modern topics in population dynamics, computer science, epidemiology, immunology, physiology, and neural networks. In this talk, we provide a wide range of delay differential models with a richer mathematical framework (compared with ODEs) for analyzing biosystems. Qualitative and quantitative features of DDEs are discussed. Some numerical simulations are also provided to show the effectiveness of the theoretical results.

A fitted numerical technique using a cubic spline in compression for the singularly perturbed Fredholm integro differential equation

RAJAGOPAL S
Research Scholar
India
Co-Author(s):    Dinesh Kumar S
Abstract:
This paper deals with the second-order Fredholm integro differential equations perturbed singularly. Similar problems arise when modelling the spatiotemporal evolution of epidemics mathematically. An fitted difference scheme on a uniform mesh is accomplished by the method based on cubic spline in compression. An analysis is conducted on the scheme`s stability. The convergence of the proposed scheme is examined. The theory is supported numerically by the solutions to several example and are presented in the table.

Synchronization of Fuzzy Reaction-Diffusion Neural Networks via Semi-intermittent Hybrid control and its application to Medical Image Encryption

Kathiresan Sivakumar
Nazarbayev University
Kazakhstan
Co-Author(s):    Mohanrasu S S, Ardak Kashkynbayev, Rakkiyappan Rajan
Abstract:
This paper addresses the problem of synchronizing fuzzy reaction-diffusion neural networks (FRDNNs) with time-varying transmission delays using aperiodic semi-intermittent hybrid controls and its application in image encryption. The main challenge in analyzing the dynamics of FRDNNs included diffusion terms with uncertainty, and the inclusion of fuzzy logic operations further increases the system`s complexity. We propose a new concept called the average control width (ACW) for aperiodic semi-intermittent control (ASIC) systems; it is used in conjunction with the idea of average dwell time (ADT) for switched systems. A sufficient flexible condition for drive-response synchronization of neural networks using average-width semi-intermittent hybrid control assures ADT and ACW conditions. By utilizing these concepts, the proposed synchronization method can overcome the challenges posed by the diffusion terms and fuzzy logic operations in FRDNNs with time-varying transmission delays. Finally, the paper presents a theoretical framework for synchronizing FRDNNs with time-varying transmission delays using semi-intermittent hybrid control via LMI and suitable Lyapunov functional, validated through simulations. The proposed synchronization method is also applied to develop a novel chaos-based elliptic curve cryptography algorithm for medical image encryption.

Non polynomial spline approach on an adaptive mesh for a weakly coupled system of singularly perturbed delay differential equations of convection diffusion type with large delay

Dinesh Kumar Subramani
Vellore Institute of Technology Vellore
India
Co-Author(s):    Dany Joy
Abstract:
This paper presents a numerical scheme for solving a weakly coupled system of singularly perturbed delay differential equations of convection diffusion type with large delay. The difference scheme on adaptive mesh is accomplished by the method which is based on non polynomial spline approach. An analysis is conducted on the scheme`s stability. The convergence of the proposed scheme is examined. To illustrate the theoretical analysis, several examples are solved for different values of the perturbation parameter, with the computational results displayed in tables are more accurate than the previous results.