Analysis of learning rate using BP algorithm for hand written digit recognition application

The objective of the research is to analyze the learning rate using BP algorithm of Artificial Neural Network (ANN) for hand written digit recognition application. In this paper the results are obtained using two variations of BP algorithm variations of Back Propagation (BP) algorithm: simple BP and BP with momentum. Different patterns of handwritten digits are used to analysis the performance of BP algorithm. Various parameters such as learning rate, number of hidden neurons in hidden layer, momentum term and number of training runs are used during the analysis of the BP algorithm. The parameters of BP algorithm are used to analyze the learning rate which shows its impact for hand written digit recognition application. Simulation results show that the learning rate affects the performance of ANN.