AbstractThis paper is concerned with existence and global exponential stability of periodic solutions for a class of Cohen–Grossberg neural networks with bounded and unbounded delays. By the continuation theorem of coincidence degree theory and differential inequality techniques, we deduce some sufficient conditions ensuring existence as well as global exponential stability of periodic solution. These conditions in our results are milder and less restrictive than that of previous known criteria since the hypothesis of boundedness and differentiability on the activation function are dropped. The theoretical analysis are verified by numerical simulations
Abstract. We study the existence and global exponential stability of posi-tive periodic solutions fo...
We study the existence and global exponential stability of positive periodic solutions for a class ...
By using coincidence degree theory as well as a priori estimates and Lyapunov functional, we study t...
AbstractThis paper is concerned with existence and global exponential stability of periodic solution...
AbstractIn this paper, Cohen–Grossberg neural networks (CGNNs) with delays are considered. Some new ...
This paper is concerned with the problem of the existence, uniqueness, and global exponential stabil...
AbstractSufficient conditions are obtained for the existence and global attractivity of periodic sol...
By using the continuation theorem of coincidence degree theory and Lyapunov functions, we study the ...
By using coincidence degree theory and Lyapunov functions, we study the existence and global expone...
In this paper, a generalized model of Cohen-Grossberg neural net-works with periodic coefficients an...
In this paper, a class of periodic Cohen-Grossberg neural networks with discrete and distributed tim...
In this paper, by using Mawhin-s continuation theorem of coincidence degree and a method based on de...
AbstractBy using the continuation theorem of Mawhins coincidence degree theory and constructing a su...
By using the method of coincidence degree theory and constructing suitable Lyapunov functional, seve...
AbstractIn this paper, the exponential periodicity and stability of neural networks with Lipschitz c...
Abstract. We study the existence and global exponential stability of posi-tive periodic solutions fo...
We study the existence and global exponential stability of positive periodic solutions for a class ...
By using coincidence degree theory as well as a priori estimates and Lyapunov functional, we study t...
AbstractThis paper is concerned with existence and global exponential stability of periodic solution...
AbstractIn this paper, Cohen–Grossberg neural networks (CGNNs) with delays are considered. Some new ...
This paper is concerned with the problem of the existence, uniqueness, and global exponential stabil...
AbstractSufficient conditions are obtained for the existence and global attractivity of periodic sol...
By using the continuation theorem of coincidence degree theory and Lyapunov functions, we study the ...
By using coincidence degree theory and Lyapunov functions, we study the existence and global expone...
In this paper, a generalized model of Cohen-Grossberg neural net-works with periodic coefficients an...
In this paper, a class of periodic Cohen-Grossberg neural networks with discrete and distributed tim...
In this paper, by using Mawhin-s continuation theorem of coincidence degree and a method based on de...
AbstractBy using the continuation theorem of Mawhins coincidence degree theory and constructing a su...
By using the method of coincidence degree theory and constructing suitable Lyapunov functional, seve...
AbstractIn this paper, the exponential periodicity and stability of neural networks with Lipschitz c...
Abstract. We study the existence and global exponential stability of posi-tive periodic solutions fo...
We study the existence and global exponential stability of positive periodic solutions for a class ...
By using coincidence degree theory as well as a priori estimates and Lyapunov functional, we study t...