A set of stability criteria for delayed cellular neural networks

This work 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, α^*_ij, β^* _ij, η^*_ij, ζ^*_ij , α_ij, β_ij, η_ij, ζ_ij∈R with α^*_ij+β ^*_ij=1, α_ij+β_ij=1, η^*_ij+ζ^*_ij=1, η _ij+ζ_ij=1(i, j=1, 2, ..., n) and combining with elementary inequality technique 2ab⩽a²+b². 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