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In this paper, we study the finite-time dissipativity analysis of Markovian jump-delayed neural networks (MJDNNs). The goal is to establish less conservative results for extended dissipativity conditions for delayed MJDNNs. To achieve this, an appropriate Lyapunov-Krasovskii functional (LKF) with novel inequality like composite slack-matrix-based integral inequality (CSMBII). Next, the CSMBII and other sufficient conditions are employed to estimate the derivative of the constructed LKF. Using these techniques, a delay-dependent finite-time dissipativity condition is derived in terms of linear matrix inequalities (LMIs). These LMIs are used to formulate the finite dissipativity condition for the delayed MJNNs. The utility of the suggested approach is then confirmed by a number of interesting numerical examples, one of which has been confirmed by a real-world application of the benchmark problem that is associated with the designed MJDNNs. The illustrative simulation results conclusively demonstrate the superior performance and success of the developed CSMBII technique in this proposal, surpassing the limitations of existing techniques.

This paper delves into a novel category of nonlocal boundary value problems concerning nonlinear sequential fractional differential equations, coupled with a unique form of generalized Riemann–Liouville fractional differential integral boundary conditions. For single-valued maps, we employ a transformation technique to convert the provided system into an equivalent fixed-point problem, which we then address using standard fixed-point theorems. Following this, we evaluate the stability of these solutions utilizing the Ulam–Hyres stability method. To elucidate the derived findings, we present constructed examples.

This work investigates the dynamic complications of the Ricker type predator-prey model in the presence of the additive type Allee effect in the prey population. In the modeling of discrete-time models, Euler forward approximations and piecewise constant arguments are the most frequently used schemes. In Euler forward approximations, the model may undergo period-doubled orbits and invariant circle orbits, even while varying the step size. In this way, differential equations with piecewise constant arguments (Ricker-type models) are a better choice for the discretization of a continuous-time model because they do not involve any step size. First, the interaction between prey and predator in the form of the Holling-Ⅱ type is considered. The essential mathematical features are discussed in terms of local stability and the bifurcation phenomenon as well. Next, we apply the center manifold theorem and normal form theory to achieve the existence and directions of flip bifurcation and Neimark-Sacker bifurcation. Moreover, this paper demonstrates that the outbreak of chaos can stabilize in the considered model with a higher value of the Allee parameter. The existence of chaotic orbits is verified with the help of a one-parameter bifurcation diagram and the largest Lyapunov exponents, respectively. Furthermore, different control methods are applied to control the bifurcation and fluctuating phenomena, i.e., state feedback, the Ott-Grebogi-Yorke, and hybrid control methods. Finally, to ensure our analytical results, numerical simulations have been carried out using MATLAB software.

In this paper, we study the Hyers-Ulam stability with respect to the linear differential condition of fourth order. Specifically, we treat ${\psi}$ as an interact arrangement of the differential condition, i.e., where ${\psi} \in c^4 [{\ell}, {\mu}], {\Psi} \in [{\ell}, {\mu}]$. We demonstrate that ${\psi}^{iv} ({\varkappa}) + {\xi}_1 {\psi}{'''} ({\varkappa})+ {\xi}_2 {\psi}{''} ({\varkappa}) + {\xi}_3 {\psi}' ({\varkappa}) + {\xi}_4 {\psi}({\varkappa}) = {\Psi}({\varkappa})$ has the Hyers-Ulam stability. Two examples are provided to illustrate the usefulness of the proposed method.

Fear and prey refuges are two significant topics in the ecological community because they are closely associated with the connectivity of natural resources. The effect of fear on prey populations and prey refuges (proportional to both the prey and predator) is investigated in the nonlinear-type predator-harvested Leslie–Gower model. This type of prey refuge is much more sensible and realistic than the constant prey refuge model. Because there is less research on the dynamics of this type of prey refuge, the current study has been considered to strengthen the existing literature. The number and stability properties of all positive equilibria are examined. Since the calculations for the determinant and trace of the Jacobian matrix are quite complicated at these equilibria, the stability of certain positive equilibria is evaluated using a numerical simulation process. Sotomayor’s theorem is used to derive a precise mathematical confirmation of the appearance of saddle-node bifurcation and transcritical bifurcation. Furthermore, numerical simulations are provided to visually demonstrate the dynamics of the system and the stability of the limit cycle is discussed with the help of the first Lyapunov number. We perform some sensitivity investigations on our model solutions in relation to three key model parameters: the fear impact, prey refuges, and harvesting. Our findings could facilitate some biological understanding of the interactions between predators and prey.

Abstract In this article, we discuss the dynamics of a Leslie–Gower ratio-dependent predator–prey model incorporating fear in the prey population. Moreover, the Allee effect in the predator growth is added into account from both biological and mathematical points of view. We explore the influence of the Allee and fear effect on the existence of all positive equilibria. Furthermore, the local stability properties and possible bifurcation behaviors of the proposed system about positive equilibria are discussed with the help of trace and determinant values of the Jacobian matrix. With the help of Sotomayor’s theorem, the conditions for existence of saddle-node bifurcation are derived. Also, we show that the proposed system admits limit cycle dynamics, and its stability is discussed with the value of first Lyapunov coefficient. Moreover, the numerical simulations including phase portrait, one- and two-parameter bifurcation diagrams are performed to validate our important findings.

Abstract This study focuses on the exponential stability and stabilization of nonlinear systems via fuzzy sampled‐data control technique. The stability and stabilization conditions are obtained through constructing suitable Lyapunov functional which contains the sampling information and the solvable linear matrix inequalities. Then, the dynamics of the nonlinear buck converter system and Lorenz system with the sampled‐data controller is analyzed and designed. Finally, the proposed method is validated with a basic buck converter system model designed to reflect the characteristics of the power metal‐oxide‐semiconductor field‐effect transistors in the numerical section. In addition, the superiority of the sufficient conditions obtained is shown by comparing with the existing methods of the Lorentz system.

Abstract This paper investigates singularly perturbed parabolic partial differential equations with delay in space, and the right end plane is an integral boundary condition on a rectangular domain. A small parameter is multiplied in the higher order derivative, which gives boundary layers, and due to the delay term, one more layer occurs on the rectangle domain. A numerical method comprising the standard finite difference scheme on a rectangular piecewise uniform mesh (Shishkin mesh) of N r × N t $N_{r} \times N_{t}$ elements condensing in the boundary layers is suggested, and it is proved to be parameter-uniform. Also, the order of convergence is proved to be almost two in space variable and almost one in time variable. Numerical examples are proposed to validate the theory.

In this paper, we present a finite-time synchronization (FTS) for quantized Markovian-jump time-varying delayed neural networks (QMJTDNNs) via event-triggered control. The QMJTDNNs take into account the effects of quantization on the system dynamics and utilize a combination of FTS and event-triggered communication to mitigate the effects of communication delays, quantization error, and efficient synchronization. We analyze the FTS and convergence properties of the proposed method and provide simulation results to demonstrate its effectiveness in synchronizing a network of QMJTDNNs. We introduce a new method to achieve the FTS of a system that has input constraints. The method involves the development of the Lyapunov–Krasovskii functional approach (LKF), novel integral inequality techniques, and some sufficient conditions, all of which are expressed as linear matrix inequalities (LMIs). Furthermore, the study presents the design of an event-triggered controller gain for a larger sampling interval. The effectiveness of the proposed method is demonstrated through numerical examples.

Abstract Dynamical analysis of a delayed tri-trophic food chain consisting of prey, an intermediate, and a top predator is investigated in this paper. The additive Allee effect is introduced in the prey population, and it is assumed that there is a time lag due to the gestation effect in the intermediate predator. The interference among the prey and the intermediate predator is according to Holling type II, while the interaction between the intermediate and top predators follows the Crowley–Martin functional response. The local stability and bifurcation analysis of the proposed model at the interior equilibrium point are studied. Numerical simulations are provided to ensure the mathematical results.

This paper deals with the extended dissipativity and non-fragile synchronization of delayed recurrent neural networks (RNNs) with multiple time-varying delays and sampled-data control. A suitable Lyapunov-Krasovskii Functional (LKF) is built up to prove the quadratically stable and extended dissipativity condition of delayed RNNs using Jensen inequality and limited Bessel-Legendre inequality approaches. A non-fragile sampled-data approach is applied to investigate the problem of neural networks with multiple time-varying delays, which ensures that the master system synchronizes with the slave system and is designed with respect to the solutions of Linear Matrix Inequalities (LMIs). The effectiveness of the suggested approach is established by providing suitable simulations using MATLAB LMI control toolbox. Finally, numerical examples and comparative results are provided to illustrate the adequacy of the planned control scheme.

In this paper, we investigate sampled-data stabilization of memristor nonlinearity in Chua's circuits. The system stability pertaining to its switching nonlinearity covers two situations of flux thresholds. Through the stability analysis, the multistability characteristic is proved by its periodic invariant stable line. Moreover, the dynamical features of the considered system are examined in details by numerical and corresponding simulated experiments. Several statistical and analytical characteristic methods are used to confirm the existence of chaotic attractors. With the help of Lyapunov stability theory, new sufficient conditions are formulated using the linear matrix inequality (LMI) method to ensure robust stability and stabilization of closed-loop systems. Finally, we present a numerical example to ascertain the validity of the theoretical results obtained.

This article examines the issue of event-triggered $L_{2}-L_\infty $ filtering for network-based neutral systems via Takagi-Sugeno (T-S) fuzzy approach. A dynamic discrete event-triggered scheme (ETS) is introduced to save the limited communication resource. Based on the T-S fuzzy model, the consider neutral type system with networked induced delays are represented as a class of T-S fuzzy system. In addition, by considering a suitable Lyapunov-Krasovskii functional (LKF) and by using the Wirtinger inequality technique, the stability conditions with respect to linear matrix inequalities (LMIs) are presented to guarantee the considered filtering systems are asymptotically stable with $L_{2}-L_{\infty }$ performance index $\gamma $ . To the end, numerical examples are given to illustrate the effectiveness of the proposed result.

Abstract This study aims to use the fractional Fourier transform for analyzing various types of Hyers–Ulam stability pertaining to the linear fractional order differential equation with Atangana and Baleanu fractional derivative. Specifically, we establish the Hyers–Ulam–Rassias stability results and examine their existence and uniqueness for solving nonlinear problems. Simulation examples are presented to validate the results.

Abstract In the current study, we conduct an investigation into the Hyers–Ulam stability of linear fractional differential equation using the Riemann–Liouville derivatives based on fractional Fourier transform. In addition, some new results on stability conditions with respect to delay differential equation of fractional order are obtained. We establish the Hyers–Ulam–Rassias stability results as well as examine their existence and uniqueness of solutions pertaining to nonlinear problems. We provide examples that indicate the usefulness of the results presented.

In this paper, we focus on the global stability analysis with respect to dynamical delayed neural networks (NNs) that contain parameter uncertainties. Many investigations on the sufficient conditions utilizing different upper bounds for the norm of interconnection matrices pertaining to the global asymptotic robust stability of delayed NNs have been conducted. In this study, a new upper bound of the norm of connection weight matrices is derived for the delayed NNs under parameter uncertainties. The key focus is on how the new upper bound is able to yield minimum result with respects to some of the existing upper bounds. We demonstrate that the new upper bound can lead to some new sufficient conditions with respect to the global asymptotic robust stability of equilibrium point of the delayed NNs. The slope bounded activation functions and Lyapunov-Krasovskii functionals (LKFs) are employed for formulating the sufficient conditions of the equilibrium point of NNs. Moreover, the derived sufficient conditions are independent on the time delay parameter. Numerical examples are provided and the outcomes obtained are compared with those of the existing results subject to different network parameters.

Impact of non-uniform heat source/sink and elastic deformation on entropy generation analysis for Cu − Fe3O4/ethylene glycol hybrid nanofluid flow past a stretching sheet with an inclined magnetic field, partial slip, and thermal radiations are investigated. Appropriate conversions are utilized for PDE's into ODE's. The dimensionless form is then analytically solved with the help of a hypergeometric function. Performance of significant variables on the hybrid nanofluid flow, heat distribution, skin friction coefficient, Nusselt number, and entropy generation are obtained and discussed with the help of different graphs. Some main results reported in this article reveals that the presents of hybrid nanoparticle, partial slip, inclined magnetic field, and Eckert number improve the more heat conduction in Cu − Fe3O4/ethylene glycol hybrid nanofluid and Partial slip, non-uniform heat source, and Eckert numbers are minimized the entropy production. Skin friction coefficient improves through higher values of Cupper nanoparticles and suction parameter. Heat transfer rate is more for higher values of Cupper nanoparticles, non-uniform heat source, partial slip, thermal radiation, and Eckert number.

The discrete-time system has more complex and chaotic dynamical behaviors as compared to the continuous-time system. This paper extends a discrete Leslie–Gower predator-prey system with the Allee effect in the predator’s population, whose dynamics are analyzed and explored. We have determined the equilibrium points and studied their local stability properties. We find that the system undergoes flip bifurcation and Neimark–Sacker bifurcation around the interior equilibrium point by choosing the Allee parameter as a bifurcation parameter. We discuss the stability and direction of both bifurcations with the help of the normal form theory and center manifold theorem. The flip bifurcation and Neimark–Sacker bifurcation are the most common routes to the chaotic orbit in the discrete system. Moreover, we utilize state feedback, pole placement, and hybrid control methods to control the chaos in the system. The work is complete with the numerical simulations to confirm the analytical findings.

This study presents an extended dissipative analysis of fractional order fuzzy networked control system with uncertain parameters. First, we designed the network-based fuzzy controller for the considered model. Second, a novel Lyapunov-Krasovskii functional (LKF) approach, inequality techniques, and some sufficient conditions are established, which make the proposed system quadratically stable under the extended dissipative criteria. Subsequently, the resultant conditions are expressed with respect to linear matrix inequalities (LMIs). Meanwhile, the corresponding controller gains are designed under the larger sampling interval. Finally, two numerical examples are presented to illustrate the viability of the obtained criteria.

We deal with a heterogeneous pharmaceutical knowledge-graph containing textual information built from several databases. The knowledge graph is a heterogeneous graph that includes a wide variety of concepts and attributes, some of which are provided in the form of textual pieces of information which have not been targeted in the conventional graph completion tasks. To investigate the utility of textual information for knowledge graph completion, we generate embeddings from textual descriptions given to heterogeneous items, such as drugs and proteins, while learning knowledge graph embeddings. We evaluate the obtained graph embeddings on the link prediction task for knowledge graph completion, which can be used for drug discovery and repurposing. We also compare the results with existing methods and discuss the utility of the textual information.

In this paper, the partial topology identification of stochastic multi-group models with multiple dispersals is investigated. Based on adaptive pinning control and a graph-theoretic method, some sufficient criteria about partial topology identification of stochastic multi-group models with multiple dispersals are obtained. That is to say, the unknown partial topological structures can be identified successfully. In the end, numerical examples are provided to verify the effectiveness of theoretical results.

In this paper, we investigate the general solution of a new quadratic functional equation of the form ∑1≤i

This paper investigates the global exponential stability of fractional order complex-valued neural networks with leakage delay and mixed time varying delays. By constructing a proper Lyapunov-functional we established sufficient conditions to ensure global exponential stability of the fractional order complex-valued neural networks. The stability conditions are established in terms of linear matrix inequalities. Finally, two numerical examples are given to illustrate the effectiveness of the obtained results.

This study investigated the flow and heat transfer of sodium alginate-based hybrid nanofluids with a stretching/shrinking surface. The heat source/sink, Joule heating, inclined magnetic field, and thermal radiation influences are also examined in the designed model. The mixers of non-magnetic and magnetic nanoparticles are utilized, such as Cu and Fe3O4. The Casson fluid model is applied to determine the viscoplastic characteristics of sodium alginate (SA). The necessary governing SA-based hybrid nanofluid flow equations are solved analytically by hypergeometric function. SA-based hybrid nanofluid velocity, temperature, skin friction, and Nusselt number results are discussed in detail with various pertinent parameters, such as radiation, heat source/sink, inclined angle, magnetic field, Eckert number, and Casson parameters. It is noted that the dimensions of both Cu and Fe3O4 hybrid nanoparticles and Casson parameters are minimized by the momentum surface layer thickness. The magnetic field, radiation, heat source and Casson parameters serve to enhance the thermal boundary layer thickness. Finally, the current result was verified with previously published works.