Coupled oscillators are highly complex dynamical systems, and it is an intriguing concept to
use this oscillator dynamics for computation. The idea is not new, but is currently the subject …

Stability problems of continuous-time recurrent neural networks have been extensively
studied, and many papers have been published in the literature. The purpose of this paper is …

This paper focuses on the promise of artificial neural networks in the realm of modelling,
identification and control of nonlinear systems. The basic ideas and techniques of artificial …

This book is about modeling, analysis, and control of dynamical systems. Its objective is to
familiarize the reader with the basics of dynamical system theory while, at the same time …

In this paper, the event-triggered state estimation problem is investigated for a class of
discrete-time multidelayed neural networks with stochastic parameters and incomplete …

The paper considers a class of additive neural networks where the neuron activations are
modeled by discontinuous functions or by continuous non-Lipschitz functions. Some tools …

Two different approaches are employed to investigate the global attractivity of delayed
Hopfield neural network models. Without assuming the monotonicity and differentiability of …

In this paper a novel approach to assess the stability of dynamic neural networks is
presented. Using a Lyapunov function, we determine conditions to guarantee input-to-state …

For neural networks with constant or time-varying delays, the problems of determining the
exponential stability and estimating the exponential convergence rate are studied in this …

Both exponential stability and periodic oscillatory solution of bidirectional associative
memory (BAM) networks with axonal signal transmission delays are considered by …