Dimirovski, Georgi M. (Dogus Author)This work is concerned with the delay-dependentstability problem for recurrent neural networks with time-varying delays. A new improved delay-dependent stability criterion expressed in terms of linear matrix inequalities is derived by constructing a dedicated Lyapunov-Krasovskii functional via utilizing Wirtinger inequality and convex combination approach. Moreover, a further improved delay-dependent stability criterion is established by means of a new partitioning method for bounding conditions on the activation function and certain new activation function conditions presented. Finally, the application of these novel results to an illustrative example from the literature has been investigated and their e...
This paper addresses the problem of asymptotic stability for discrete-time recurrent neural networks...
The robust stability of uncertain discrete-time recurrent neural networks with time-varying delay is...
This paper presents some results on the global exponential stabilization for neural networks with va...
This note investigates the problem of exponential stability of neural networks with time-varying del...
This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying d...
Together with Lyapunov-Krasovskii functional theory and reciprocal convex technique, a new sufficien...
Dimirovski, Georgi M. (Dogus Author)In this brief, a novel partitioning method for the conditions on...
This is the post print version of the article. The official published version can be obtained from t...
This paper is concerned with the stability analysis of discrete-time neural networks with a time-var...
In this paper, the asymptotic stability problem of neural networks with time-varying delays is inves...
By using the fact that the neuron activation functions are sector bounded and nondecreasing, this br...
Copyright © 2014 Lei Ding et al.This is an open access article distributed under the Creative Common...
[[abstract]]A global stability analysis of a particular class of recurrent neural networks with time...
This is the post print version of the article. The official published version can be obtained from t...
This paper discusses stability of neural networks (NNs) with time-varying delay. Delay-fractioning L...
This paper addresses the problem of asymptotic stability for discrete-time recurrent neural networks...
The robust stability of uncertain discrete-time recurrent neural networks with time-varying delay is...
This paper presents some results on the global exponential stabilization for neural networks with va...
This note investigates the problem of exponential stability of neural networks with time-varying del...
This paper deals with the stability of static recurrent neural networks (RNNs) with a time-varying d...
Together with Lyapunov-Krasovskii functional theory and reciprocal convex technique, a new sufficien...
Dimirovski, Georgi M. (Dogus Author)In this brief, a novel partitioning method for the conditions on...
This is the post print version of the article. The official published version can be obtained from t...
This paper is concerned with the stability analysis of discrete-time neural networks with a time-var...
In this paper, the asymptotic stability problem of neural networks with time-varying delays is inves...
By using the fact that the neuron activation functions are sector bounded and nondecreasing, this br...
Copyright © 2014 Lei Ding et al.This is an open access article distributed under the Creative Common...
[[abstract]]A global stability analysis of a particular class of recurrent neural networks with time...
This is the post print version of the article. The official published version can be obtained from t...
This paper discusses stability of neural networks (NNs) with time-varying delay. Delay-fractioning L...
This paper addresses the problem of asymptotic stability for discrete-time recurrent neural networks...
The robust stability of uncertain discrete-time recurrent neural networks with time-varying delay is...
This paper presents some results on the global exponential stabilization for neural networks with va...