特集「物理リザバー・コンピューティング」
固体電解質を用いた物理リザバー
2024 年 67 巻 11 号 p. 521-526
詳細
2024 年 67 巻 11 号 p. 521-526
A solid electrolyte-based physical reservoir utilizes ions’ diffusion and their redox reactions to achieve nonlinear transformation of input and its short-term memorization. One of the major advantage in using a solid electrolyte is easy fabrication of a recurrent neural network with a large number of ‘nodes’, which enables various functions unique to the material-based physical reservoir such as in-sensor computing.
