Neural network for the reliability analysis of simplex systems

Abstract A new approach to the reliability analysis, based on neural networks, is introduced in this paper. The reliability analysis of a simple nonredundant digital system, Simplex System, with repair is used to illustrate the neural network approach. The discrete-time Markov model of simplex systems is realized using feed-forward recursive neural network. The energy function and update equations for the weights of the neural network are estabilished such that the network converges to the desired reliability of the simplex system under design. The failure rate and repair rate, satisfying the desired reliability, are extracted from the neural weights at convergence. The obtained results are verified by the conventional approach.