  The stability and convergence of the neural networks are the fundamental
characteristics in the Hopfield type networks. Since time delay is ubiquitous
in most physical and biological systems, more attention is being made for the
delayed neural networks. The inclusion of time delay into a neural model is
natural due to the finite transmission time of the interactions. The stability
analysis of the neural networks depends on the Lyapunov function and hence it
must be constructed for the given system. In this paper we have made an attempt
to establish the logarithmic stability of the impulsive delayed neural networks
by constructing suitable Lyapunov function.
