A set of stability criteria for delayed cellular neural networks

This brief presents a set of criteria on the global asymptotic stability of delayed cellular neural networks (DCNN) by constructing suitable Lyapunov functionals, introducing ingeniously real parameters w(i) > 0, alpha (ij)*, beta (ij)*, eta (ij)*, zeta (ij)*, alpha (ij), beta (ij), eta (ij), zeta (ij) is an element of R with alpha (ij)* + beta (ij)* = 1, alpha (ij) + beta (ij) = 1,eta (ij)* + zeta (ij)* = 1,eta (ij) + zeta (ij) = 1 (i, j = 1, 2,...,n) and combining with elementary inequality technique 2ab less than or equal to a(2) + b(2). These criteria are of theoretical and applicable important significance in signal processing, especially in speed detection of moving objects, processing of moving images and the design of networks since they possess infinitely adjustable real parameters. This result is also discussed from the point of view of its relationship to earlier results.