Global asymptotic stability of delayed Cohen-Grossberg neural networks (Q2471198)

The authors consider a class of Cohen-Grossberg neural networks given by the delayed dynamical system \[ {dx_i(t)\over dt}= -a_i(x_i(t))\Biggl[b_i(x_i(t))- \sum^n_{j=1} a_{ij} f_j(x_j(t))- \sum^n_{j=1} a^\tau_{ij} f_j(x_j(t- \tau_j(t)))+ I_i\Biggr], \] \(i= 1,2,\dots, n\), where \(A= (a_{ij})_{n\times n}\) and \(A^\tau= (a^\tau_{ij})_{n\times n}\) are the connection weight matrix and the delayed connection matrix respectively. As a main result, new sufficient conditions for the uniqueness and global asymptotic stability of the equilibrium point of the system are obtained. An example, which shows the comparison to previous results, is given.