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 …

The stability analysis of recurrent neural networks (RNNs) with multiple equilibria has
received extensive interest since it is a prerequisite for successful applications of RNNs …

A concise tutorial description of the cellular neural network (CNN) paradigm is given, along
with a precise taxonomy. The CNN is defined, and the canonical equations are described …

Revolutionary and original, this treatise presents a new paradigm of Emergence and
Complexity, with applications drawn from numerous disciplines, including artificial life …

Cellular Nonlinear/neural Network (CNN) technology is both a revolutionary concept and an
experimentally proven new computing paradigm. Analogic cellular computers based on …

In this paper, the existence and uniqueness of the equilibrium point and its global asymptotic
stability are discussed for a general class of recurrent neural networks with time-varying …

In this paper, two related problems, global asymptotic stability (GAS) and global robust
stability (GRS) of neural networks with time delays, are studied. First, GAS of delayed neural …

In this paper, the global exponential stability and periodicity for a class of reaction–diffusion
delayed recurrent neural networks with Dirichlet boundary conditions are addressed by …

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 …

In this paper, a novel method is developed for the stability problem of a class of neural
networks with time-varying delay. New delay-dependent stability criteria in terms of linear …