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Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
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工业数据序列建模的等级自我注意网络,在输入和输出序列之间具有不同的采样速率

Xiaofeng Yuan, Zhenzhen Jia, Zijian Xu

    IEEE transactions on neural networks and learning systems
    |April 24, 2024
    PubMed
    概括

    这项研究引入了一个层次化的自我注意网络 (HSAN),通过利用所有数据,即使采样率不同,来改善工业质量预测. 这种新的方法增强了动态建模和变量相互作用分析,以获得更准确的预测.

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