Associative Memories Using Interaction between Multilayer Perceptrons and Sparsely Interconnected Neural Networks(Special Section on Papers Selected from ITC-CSCC 2001)

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概要

• 論文の詳細を見る

• Associative memories composed of sparsely interconnected neural networks (SINNs) are suitable for analog hardware implementation. However, the sparsely interconnected structure also gives rise to a decrease in the capability of SINNs for associative memories. Although this problem can be solved by increasing the number of interconnections, the hardware cost goes up rapidly. Therefore, we propose associative memories consisting of multilayer perceptrons (MLPs) with 3-valued weights and SINNs. It is expected that such MLPs can be realized at a lower cost than increasing interconnections in SINNs and can give each neuron in SINNs the global information of an input pattern to improve the storage capacity. Finally, it is confirmed by simulations that our proposed associative memories have good performance.

• 社団法人電子情報通信学会の論文
• 2002-06-01

著者

• Kamio T

  Hiroshima City Univ. Hiroshima

• Kamio Takeshi

  Faculty Of Engineering Shizuoka University

• Morisue M

  Hiroshima City Univ. Hiroshima‐shi Jpn

• Morisue Mititada

  Faculty Of Engineering Saitama University

• Fujisaka H

  Hiroshima City Univ. Hiroshima‐shi Jpn

• Fujisaka Hisato

  Faculty Of Information Sciences Hiroshima City University

• Fujisaka Hisato

  Faculty of Information Science, Hiroshima City University

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• FOREWORD
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