Character Recognition Using BP Neural Networks

Character recognition based on Backpropagation Neural Networks. The BP neural network algorithm transforms input-output sample problems into nonlinear optimization problems and solves weight values through iterative gradient descent operations. This implementation uses BP networks for classification with supplemental linear perceptrons for effective single-character recognition. The algorithm features straightforward implementation, high recognition accuracy, and robust performance in various high-noise environments for printed character recognition. Key implementation aspects include gradient computation, weight updating mechanisms, and activation function configuration.