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 …

This brief is concerned with the problem of asymptotic stability of neural networks with time-
varying delays. The activation functions are monotone nondecreasing with known lower and …

In this letter, the delay-dependent state estimation problem for neural networks with time-
varying delay is investigated. A delay-dependent criterion is established to estimate the …

In the paper, the global asymptotic stability of equilibrium is considered for continuous
bidirectional associative memory (BAM) neural networks of neutral type by using the …

In this paper, a new delay-dependent asymptotic stability condition for delayed Hopfield
neural networks is given in terms of a linear matrix inequality, which is less conservative …

This paper is concerned with the problem of finite-time boundedness, L 2 gain analysis and
control of Markovian jump switched neural networks (MJSNNs) with additive time-varying …

This book addresses the new models in mathematical neuroscience and artificial neural
networks, which have many similarities with the structure of the human brain and the …

A new Lyapunov-Krasovskii functional is constructed for delayed cellular neural networks,
and the S-procedure is employed to handle the nonlinearities. An improved global …

The problem of stochastic robust stability of a class of stochastic Hopfield neural networks
with time-varying delays and parameter uncertainties is investigated in this paper. The …

In this paper, robust stability problems for interval Cohen-Grossberg neural networks with
unknown time-varying delays are investigated. Using linear matrix inequality, M-matrix …