Abstract

Now is the age of neuromorphic computing that creates brain circuits. The analog and digital circuit theory changes because the values of the basic conductance elements can be made variable by learning. The computer structure changes to in-memory computing technology in cooperation with a von Neumann architecture. In this paper, we propose a gyrator neuron (GN) that enables analog computer operations by nodal equation. The GN is constructed based on memristor elements. The GN executes learning by back propagation processing and association by forward propagation processing.

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