Nowadays, neural networks have been widely applied in many fields such as pattern
recognition, signal and image processing and control theory. Over the past two decades or …

This paper is concerned with analysis problem for the global exponential stability of a class
of recurrent neural networks (RNNs) with mixed discrete and distributed delays. We first …

This paper introduces a general class of neural networks with arbitrary constant delays in
the neuron interconnections, and neuron activations belonging to the set of discontinuous …

By employing the Lyapunov-Krasovskii functional and linear matrix inequality (LMI)
approach, the problem of global asymptotical stability is studied for recurrent neural …

In this article, a generalized model of neural networks involving time-varying delays and
impulses is considered. By establishing the delay differential inequality with impulsive initial …

In this paper, the Cohen–Grossberg neural network model with both time-varying and
continuously distributed delays is considered. Without assuming both global Lipschitz …

Stability is considered for a class of fuzzy cellular neural networks with distributed delay. The
condition for feedback kernel is minimal: the only condition required is that∫ 0τk (s) ds= 1 …

This paper investigates global exponential stability of a class of Clifford-valued recurrent
neural networks. By using Brouwer's fixed point theorem, the existence of the equilibrium …

Both exponential stability and periodic oscillatory solutions are considered for reaction–
diffusion recurrent neural networks with continuously distributed delays. By constructing …

This paper is concerned with the analysis problem for the globally asymptotic stability of a
class of stochastic neural networks with finite or infinite distributed delays. By using the delay …