Projection rule is a powerful learning scheme for embedding patterns onto Hopfield‐type associative memories, but this cannot be used for non‐fully connected networks, such as bidirectional associative memory. This paper presents a novel type of Projection rule that can embed patterns onto partially connected networks. The applicability and performances of the proposed Projection rule are evaluated through numerical experiments. From experimental results, it is confirmed that the proposed scheme actually works on partially connected networks, though the embedding capability is not high with compared to the one in fully connected networks. It is also shown that gray‐scaled images can be embedded and retrieved in the networks. © 2020 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

中文翻译：

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具有部分连接的复值关联内存的投影规则

投影规则是一种强大的学习方案，可以将模式嵌入到Hopfield类型的关联存储器中，但是不能用于非完全连接的网络，例如双向关联存储器。本文提出了一种新型的投影规则，可以将模式嵌入到部分连接的网络中。通过数值实验评估了所提出投影规则的适用性和性能。从实验结果可以确认，尽管与完全连接网络中的嵌入能力相比，该方案实际上在部分连接的网络中有效，但是其嵌入能力并不高。还显示可以在网络中嵌入和检索灰度图像。©2020日本电气工程师学会。由Wiley Periodicals LLC发布。