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A neural network model for cursive script - Boston University

A neural network model for cursive script - Boston University 2025

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The document presents a neural network model, named the VITEWRITE model, designed for generating cursive handwriting movements. It integrates a sequential motor program with a trajectory generator to control hand movements with redundant degrees of freedom. The model utilizes the Vector Integration to Endpoint (VITE) framework to produce smooth, curvilinear trajectories that reflect complex handwriting dynamics. Key features include the ability to scale speed and size of handwriting while maintaining shape invariance, and it addresses the coordination of multiple motor synergies during writing. The findings suggest that this model can effectively replicate psychophysical properties observed in human handwriting.

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