Abstract
The purpose of this study is to construct a new model for handwritten character generation using neural networks. This model can generate not only trained characters as the handwritten-character-generation-models proposed formerly, but also untrained characters by combining radicals. The proposed model uses the neural networks with back-propagation training for generating the radicals of characters and also for estimating the features of untrained characters which signify the peculiarities of each individual hand-writing. The basic experiments verified the validity of the model.
