An artificial synapse device based on photoelectrically coupled memristor and its modulation method

Abstract

The invention discloses an artificial synapse device based on a photoelectric coupling memristor and a modulation method thereof. The artificial synapse device includes an upper electrode, a lower electrode, and a functional material layer between the upper and lower electrodes. The layer material and the lower electrode together form a sandwich structure; among them, the functional material layer is made of a material with photoconductive effect, and the lower electrode is a transparent conductive electrode; the electrical signal is input through the upper electrode and the lower electrode, and the optical signal is input through the transparent conductive electrode. The artificial synapse device provided by the present invention introduces light as the other end control signal outside the electrical signal, and expands the control end of the two-terminal artificial synapse device to three ends; this added end makes the artificial synapse device available in The resistance value changes under the external optical excitation signal. Through the selection and regulation of the optical excitation signal intensity, frequency and optical pulse time, the artificial synapse device can be configured into corresponding multiple resistance states, and various synaptic plasticity functions can be realized correspondingly. .

Description

technical field [0001] The invention belongs to the technical field of artificial neural networks, and more specifically relates to an artificial synapse device based on a photoelectric coupling memristor and a modulation method thereof. Background technique [0002] The existing Von Neumann computer architecture separates data storage and calculation, and data transmission is performed between the memory and the processor through the transmission bus, and its transmission speed will greatly limit the speed of the computer. In the era of big data, the large-scale parallel computing of massive real-time data brings challenges to the existing computing architecture. In the human brain nervous system, computation and storage can be performed simultaneously. Therefore, the research on brain-like computing is expected to become the most effective solution to break through the von Neumann bottleneck. In the human brain nervous system, information processing and storage units are...

AI Technical Summary

Problems solved by technology

At present, the research on artificial synaptic devices is focused on two-terminal synaptic devices; this not only restricts the regulation range and regulation accuracy of a single synaptic device to a certain extent, but also limits the neural synaptic devices in artificial neural networks. cross-connect

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