Among the many applications that have been proposed for neural networks, character recognition has been one of the most successful. Compared to other methods used in pattern recognition, the advantage of neural networks is that they offer a lot of flexibility to the designer, i.e. expert knowledge can be introduced into the architecture to reduce the number of parameters determined by training by examples. In this paper, a general introduction to neural network architectures and learning algorithms commonly used for pattern recognition problems is given. The design of a neural network character recognizer for on-line recognition of handwritten characters is then described in detail.
Task-space regulation of rigid-link electrically-driven robots with uncertain kinematics using neural networks