A discrete-time recurrent neural network for shortest-path routing

Presents a discrete-time recurrent neural network for solving the shortest path problem. The proposed discrete-time recurrent neural network, is proven to be globally convergent to an exact solution. In addition, the proposed neural network has fixed design parameters and simple architecture, thus is more suitable for hardware implementation. Furthermore, an improved network with a larger step size is proposed to increase the convergence rate. The performance and operating characteristics of the proposed neural network are demonstrated by means of simulation results