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引用次数: 3

摘要

提出了一种基于优化原理的计算手写模型。计算理论、表示层次和硬件分别为最小指令转矩变化准则、从手写字符中提取的一组过点和正逆松弛神经网络模型。然而,对于模型中的过点表示,同时需要时间和空间信息。在本文中,我们提出了一个新的模型,该模型通过优化准则来估计通过过点的时间。对该模型进行了理论研究,结果表明,该模型生成的轨迹与人体实验数据一致。
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A computational model for arm trajectory formation by optimization of via-point time
Proposes a computational handwriting model based on the optimization principle. The computational theory, the representation level and the hardware involved are the minimum commanded torque-change criterion, a set of via-points extracted from handwritten characters and a forward-inverse-relaxation neural network model, respectively. However, for via-point representation in the model, both timing and spatial information are needed. In this paper, we propose a new model in which the time passing through via-points is estimated by optimizing the criterion. The model is studied theoretically, and it is shown that the trajectory generated by the model is the same as the data obtained from human subjects in experiments.
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