On global stability criterion for neural networks with discrete and distributed delays

Design of delay-dependent state estimator for discrete-time recurrent neural networks with interval discrete and infinite-distributed time-varying delays

“…Therefore, the problem of stability analysis for delayed neural networks is of great importance and has attracted considerable attention. A great number of results related to this issue have been reported in the past few years (Cao and Wang 2005;Hu and Wang 2006;Shi et al 2007;Cao et al 2007;Yu et al 2003;Xu et al 2005;Arik 2003;Park 2006;Shen and Wang 2008;Cao and Wang 2003;Qi 2007;Jiao and Wang 2010;Jiao and Wang 2007). It is worth pointing out that the distributed delay occurs very often in reality and it has been an attractive subject of research in the past few years.…”

Delay-dependent stability for uncertain cellular neural networks with discrete and distribute time-varying delays

“…In other words, it is often the case that the neural network model possesses both discrete and distributed delays [7]. Recently, the stability of CNNs with discrete and distributed delays has been investigated in [13][14][15][16]. Very recently, the parametric uncertainties, which often break the stability of systems, are considered in the works [14][15][16].…”

“…The delay in the desired networks influences on the stability and occasionally causes the oscillation and poor performance of the network. Therefore, there have been many efforts to the study for the stability analysis of delayed Cellular Neural Networks (DCNNs) [4][5][6][7][8][9][10][11][12][13][14][15][16] during the last decade.…”

Global robust exponential stability analysis for stochastic interval neural networks with time-varying delays

“…The delay is a source of instability and oscillatory response of networks, so the stability analysis of neural networks with delays attracts many researchers. Many important results have been reported on the existence, uniqueness, and global asymptotic or exponential stability of the equilibrium point for neural networks with constant delays or time-varying delays, see [1][2][3][4][5][6][7][8][9][10] and the references therein for some recent publications.…”