Global stability analysis of a general class of discontinuous neural networks with linear growth activation functions

Global stability analysis in Cohen–Grossberg neural networks with delays and inverse Hölder neuron activation functions

“…Over the past decades, different classes of neural networks have attracted the attention of researchers, due to their wide range of applications in classification, system control, parallel computing, associate memory and optimization problems [10,12,14,15]. Among them, the research on Cohen-Grossberg neural networks is an important topic (see [3][4][5]9,13,19]), since this neural network could include a lot of models from evolutionary theory, population biology and neurobiology.…”

New results on synchronization control of delayed memristive neural networks

“…In these years, the stability and synchronization of nonlinear dynamical systems have been successfully applied to many areas for image processing, information science and so on, see, e.g., see [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. In addition, by using synchronization to communication will strengthen the security and secrecy when transmitting the digital signals.…”

Exponential lag synchronization for delayed memristive recurrent neural networks

“…As it is well known, stability and control in nonlinear science has been known for a rather long time, and its applications to diverse areas such as secure communications, energy system, and biological reactions, e.g., see [18][19][20][21][22][23][24][25][26][27][28][29][30][31]. Transmission delay is ubiquitous when signals are communicated among neurons, e.g., in the signal transmission system, the signal one gets on the receiver side at time t þ τ is the signal from the transmitter side at time t. So, it is reasonable to require one neural network to synchronize the other neural network at a constant time lag.…”