二维深度神经网络及其在线快速学习

2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) Pub Date : 2019-09-01 DOI:10.1109/IDAACS.2019.8924281

Yevgeniy V. Bodyanskiy, O. Boiko, I. Pliss, V. Volkova

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引用次数: 1

摘要

本文提出了二维深度神经网络及其在线学习算法。由于拒绝矢量化-去分散化操作，该系统可以减少可调节权重的数量。因此，它将数据输入的列和行之间包含的信息保存为2D矩阵。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2D-Deep Neural Network and Its Online Rapid Learning

In the paper, the 2D-deep neural network and the algorithm for its online learning are proposed. This system allows reducing the number of adjustable weights due to the rejection of the vectorization-devectorization operations. As a result, it saves the information that is contained between columns and rows of data inputs presented as 2D matrix.

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2019 10th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS)

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