Epidemic Model and Mathematical Study of Impact of Vaccination for the Control of Malware in Computer Network

Malware remains a significant threat to computer network. In this paper, we consideredthe problem which computer malware cause to personal computers with its control by proposing a compartmental model SVEIRS (Susceptible Vaccinated-Exposed-infected-Recovered-Susceptible) for malware transmission in computer network using nonlinear ordinary differential equation. Through the analysis of the model, the basic reproduction number were obtained, and the malware free equilibrium was proved to be locally asymptotical stable if is less than unity and globally asymptotically stable if Ro is less than some threshold using a Lyapunov function. Also, the unique endemic equilibrium exists under certain conditions and the model underwent backward bifurcation phenomenon. To illustrate our theoretical analysis, some numerical simulation of the system was performed with RungeKutta fourth order (KR4) method in Mathlab. This was used in analyzing the behavior of different compartments of the model and the results showed that vaccination and treatment is very essential for malware control.

Switching control for coordinated maneuvering of vehicular platoon with sensor failures

The problem of nonlinear platoon control with sensor failure is studied in this paper. First, a vehicular platoon model involving sensor failure and nonlinearity is established, in which the nonlinear platoon is divided to a linearized model in addition to a nonlinear term. Then, based on the nonlinear model, a switching controller design method is proposed by using a discrete Lyapunov function and then the sufficient state feedback control law is achieved. It is shown that the obtained control scheme can achieve asymptotical stable. Simulations are given to show the efficiency of the proposed methods.

State-Dependent Pulse Vaccination and Therapeutic Strategy in an SI Epidemic Model with Nonlinear Incidence Rate

In this paper, the state-dependent pulse vaccination and therapeutic strategy are considered in the control of the disease. A pulse system is built to model this process based on an SI ordinary differential equation model. At first, for the system neglecting the impulse effect, we give the classification of singular points. Then for the pulse system, by using the theory of the semicontinuous dynamic system, the dynamics is analyzed. Our analysis shows that the pulse system exhibits rich dynamics and the system has a unique order-1 homoclinic cycle, and by choosing p as the control parameter, the order-1 homoclinic cycle disappears and bifurcates an orbitally asymptotical stable order-1 periodic solution when p changes. Numerical simulations by maple 18 are carried out to illustrate the theoretical results.

New Theorem for Asymptotically Stability for Time-Delayed Systems Based on LMI

This paper stadies the problem of the asymptotical stability for a time-delayed systems. By using LMI method, a new approach is used to derive a delay-dependent sufficient condition, which can guarantee that the time-delayed systems with multiple time delays is asymptotical stable. At last, a numberical example is given to show that the new theorem is more effective than the present methods.

Dynamic Analysis of an SEIR Model with Distinct Incidence for Exposed and Infectives

An SEIR model with vaccination strategy that incorporates distinct incidence rates for the exposed and the infected populations is studied. By means of Lyapunov function and LaSalle’s invariant set theorem, we proved the global asymptotical stable results of the disease-free equilibrium. The sufficient conditions for the global stability of the endemic equilibrium are obtained using the compound matrix theory. Furthermore, the method of direct numerical simulation of the system shows that there is a periodic solution, when the system has three equilibrium points.

Without Diagonal Nonlinear Requirements: The More GeneralP-Critical Dynamical Analysis for UPPAM Recurrent Neural Networks

Continuous-time recurrent neural networks (RNNs) play an important part in practical applications. Recently, due to the ability of assuring the convergence of the equilibriums on the boundary line between stable and unstable, the study on the critical dynamics behaviors of RNNs has drawn especial attentions. In this paper, a new asymptotical stable theorem and two corollaries are presented for the unified RNNs, that is, the UPPAM RNNs. The analysis results given in this paper are under the generallyP-critical conditions, which improve substantially upon the existing relevant critical convergence and stability results, and most important, the compulsory requirement of diagonally nonlinear activation mapping in most recent researches is removed. As a result, the theory in this paper can be applied more generally.

Dynamic Behavior for an SIRS Model with Nonlinear Incidence Rate and Treatment

This paper considers an SIRS model with nonlinear incidence rate and treatment. It is assumed that susceptible and infectious individuals have constant immigration rates. We investigate the existence of equilibrium and prove the global asymptotical stable results of the endemic equilibrium. We then obtained that the model undergoes a Hopf bifurcation and existences a limit cycle. Some numerical simulations are given to illustrate the analytical results.

Dynamics Analysis of an SEIQS Model with a Nonlinear Incidence Rate

This paper considers an SEIQS model with nonlinear incidence rate. By means of Lyapunov function and LaSalle’s invariant set theorem, we proved the global asymptotical stable results of the disease-free equilibrium. It is then obtained the sufficent conditions for the global stability of the endemic equilibrium by the compound matrix theory. In addition, we also study the phenomena of limit cycle of the systems with the numerical simulations.