This paper proposes a model to learn Farsi handwriting in different sizes based on human behavior. This model copies a human handwritten character with imitation. The imitation includes two stages of perception and action. During the perception, the information that is needed in order to generate the character is extracted from the original pattern and during the action, the model generates a character similar to the original one. To rewrite a given character, first it is decomposed into the consecutive strokes. Each stroke is approximated by several linear subdivisions. We considered the slopes and lengths of these subdivisions as the features of a given handwriting. The model learns to write a character by learning to reproduce these features. These features are descriptive of the human handwriting behavior. The learning process becomes complete when all points of the character's trajectory have distance less than a specified distance with the original trajectory. This specified distance describes visual attention and is defined as the attention width. Attention width demonstrates the human accuracy during the different trials of learning. In our model, visual attention is adaptive and decreases as the learning progresses. After the completion of learning, Farsi letters with different sizes can be generated using only memory. In order to evaluate the performance of the model, the correlation between the original and simulated characters is used. The simulation results showed good performance of the model between different Farsi characters.