Organic material that learns

DOI Web Site
  • AKAI-KASAYA Megumi
    Graduate School of Science, Osaka University Graduate School of Information Science and Technology, Hokkaido University
  • ASAI Tetsuya
    Graduate School of Information Science and Technology, Hokkaido University
  • NAKAJIMA Kohei
    Graduate School of Information Science and Technology, The University of Tokyo

Bibliographic Information

Other Title
  • 学習する有機材料
  • 学習する有機材料 : リザバー計算に向けたニューラルネットワーク形成
  • ガクシュウ スル ユウキ ザイリョウ : リザバー ケイサン ニ ムケタ ニューラルネットワーク ケイセイ
  • Construction of physical neural networks for reservoir computing
  • リザバー計算に向けたニューラルネットワーク形成

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Description

<p>The possibility of a neural network structure utilizing any response from devices, materials or physical substances, for which a function can be used for information processing, is now attracting considerable attention. The realization of a neural network consisting of materials requires experimental processes and knowledge that might not be common in the research field of applied physics. We demonstrated the structure of two different types of neural networks utilizing the plasticity of polymer growth and the nonlinear response of the electrochemical reaction of molecules. Our organic neural networks show primitive functionality for information processing. In this paper, the system of basic neural network and reservoir computing are illustrated and explained in plain words, and experimental processes, namely, how the materials learn to be a neural network and how we evaluate their performance, are concretely explained.</p>

Journal

  • Oyo Buturi

    Oyo Buturi 90 (8), 504-508, 2021-08-05

    The Japan Society of Applied Physics

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