[12p-W933-1~11] 31.1 フォーカストセッション「AIエレクトロニクス」

▲ [12p-W933-9] Two-bit input binary task with reservoir computing using nanomagnet array

〇Kazuki Tsujimoto¹、Hikaru Nomura¹、Taishi Furuta¹、Yuki Kuwabiraki¹、Ryoichi Nakatani¹、Yoshishige Suzuki¹ (1.Osaka Univ.)

キーワード：reservoir computing, macro-spin simulation

Neural network has made great achievements in recent years. However, a general neural network implemented on a CPU/GPU has a problem of power consumption. To reduce the power consumption, reservoir computing which use physical phenomenon for numerical calculation has been reported. Recently we demonstrated reservoir computing with nanomagnet array reservoir. In this reservoir computing, static magnetization of the nanomagnets in the reservoir are used as node state. Each node state are connected via dipole field of the nanomagnets. This reservoir can perform single-bit input binary tasks. However, more complex tasks such as image recognition require not a single-bit input but a multi-bit input.
In this presentation, we demonstrate reservoir computing with two-bit binary task using a nanomagnet array as a reservoir. We performed macro-spin simulations. As a results, an output matrix of this reservoir can be trained to perform two-bit binary input tasks with delay up to one.