On stability of delayed cellular neural networks

A set of sufficient criteria are found ensuring the global asymptotic stability of delayed cellular neural networks (DCNN) with more general output functions by introducing ingeniously real parameters alpha(j)*, beta(j)*, eta(j)*, zeta(j)*, alpha(j), beta(j), eta(j), zeta(j), with alpha(j)* + beta(j)* = 1, alpha(j) + beta(j) = 1, eta(j)*, zeta(j)* = 1, eta(j) + zeta(j) = 1 (j = 1, 2, ... , n), constructing suitable Lyapunov functionals and applying some analysis techniques. These criteria are independent of delays and possess infinitely adjustable real parameters, which are of theoretical and applicable important significance in signal processing, especially in moving image treatment and the design of networks. (C) 1999 Elsevier Science B.V. All rights reserved.