Dynamics of neural networks with variable coefficients and time-varying delays

Stability analysis of a novel epidemics model with vaccination and nonlinear infectious rate

In this paper, by considering pathogen evolution and human interventions behaviors with vaccines or drugs, we build up a novel SEIRW model with the vaccination to the newborn children. The stability of the SEIRW model with time-varying perturbation to predict the evolution tendency of the disease is analyzed. Furthermore, we introduce a time-varying delay into the susceptible and infective stages in the model and give some global exponential stability criteria for the time-varying delay system. Finally, numerical simulations are presented to verify the results.

PERIODICITY AND STABILITY IN RECURRENT CELLULAR NEURAL NETWORKS WITH IMPULSIVE EFFECTS

In this paper, the exponential stability analysis problem is considered for a class of impulsive recurrent cellular neural networks (IRCNNs) with time-varying delays. Without assuming the boundedness on the activation functions, some sufficient conditions are derived for checking the existence and exponential stability of periodic solution for this system by using Mawhin's continuation theorem of coincidence degree theory and constructing suitable Lyapunov functional. It is believed that these results are significant and useful for the design and applications of IRCNNs. Finally, an example with numerical simulation is given to show the effectiveness of the proposed method and results.