Global Hyperbolic Hopfield Neural Networks

DOI Web Site 被引用文献1件 参考文献35件

書誌事項

公開日
2016
DOI
  • 10.1587/transfun.e99.a.2511
公開者
一般社団法人 電子情報通信学会

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説明

<p>In recent years, applications of neural networks with Clifford algebra have become widespread. Hyperbolic numbers are useful Clifford algebra to deal with hyperbolic geometry. It is difficult when Hopfield neural network is extended to hyperbolic versions, though several models have been proposed. Multistate or continuous hyperbolic Hopfield neural networks are promising models. However, the connection weights and domain of activation function are limited to the right quadrant of hyperbolic plane, and the learning algorithms are restricted. In this work, the connection weights and activation function are extended to the entire hyperbolic plane. In addition, the energy is defined and it is proven that the energy does not increase.</p>

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