Unit, device and method for simulating biological neuronal synapsis

Abstract

The invention discloses a unit, a device and a method for simulating biological neuronal synapsis on the basis of chalcogenide compounds. The unit comprises a first electrode layer, a function material layer and a second electrode layer, wherein the first electrode layer receives first pulse signals, and the second electrode layer receives second pulse signals. A device can change electric conductance simulation synapsis weight changes according to input signals. When the difference value between the frequency of the first pulse signals and the frequency of the second pulse signals is plus or minus, the electric conductance is changed , and the simulation of the pulse frequency dependent synaptic plasticity function of the biological neuronal synapsis is realized. When the signal difference peak value between the first pulse signals and the second pulse signals is plus or minus, the electric conductance is changed, and the simulation of the pulse time dependent synaptic plasticity function of the biological neuronal synapsis is realized. The unit, the device and the method have the advantages that the basic function of the biological neuronal synapsis can be realized on single inorganic devices, the basic device forming the artificial neural network can be provided, and the effects of integration degree improvement and power consumption reduction can be obtained.

Description

technical field [0001] The invention belongs to the field of microelectronic devices, and more specifically relates to a unit, device and method for simulating biological synapses. Background technique [0002] In a traditional computer based on the von Neumann architecture, the processor and the memory are separated and connected by a bus. Such a structure has the so-called "von Neumann bottleneck", which makes it difficult to adapt to the current era of rapid development of information technology with explosive growth of information. [0003] Compared with von Neumann computers, the neural information activities of the human brain have the characteristics of large-scale parallelism, distributed storage and processing, self-organization, self-adaptation and self-learning. Researchers in the fields of traditional artificial neural networks and neuromorphic engineering have also been working on using nonlinear circuits, FPGA, VLSI and other means to simulate the basic bioele...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the defects of the prior art, the purpose of the present invention is to provide a unit for simulating biological synapses, aiming to solve the problem that only multiple components can realize the function of a synapse

Images