Self-adaptive neuron circuit based on memristor

Abstract

The invention provides a self-adaptive neuron circuit based on a memristor. The self-adaptive neuron circuit comprises an excitation pulse, a non-volatile memristor and a capacitor; a volatile memristor, the capacitor and the resistor form a discharge loop; voltage signals at the two ends of the resistor serve as output pulses of the neuron circuit. The working process is as follows: after the nonvolatile memristor receives an excitation pulse, the capacitor is charged through the charging loop, the voltage of the capacitor is gradually increased, when the voltage at the two ends of the volatile memristor is smaller than a threshold voltage, the output pulse is 0, and when the voltage at the two ends of the volatile memristor is larger than or equal to the threshold voltage, the capacitor is discharged through the discharging loop. Voltages at two ends of the resistor serve as output pulses to generate action potentials. Under the action of the excitation pulse, the resistance value of the nonvolatile memristor is gradually increased, so that the frequency of the generated action potential is gradually reduced, and the characteristic that neurons gradually adapt to constant external stimulation is simulated. According to the invention, the adaptive function of neurons is simulated.

Description

technical field [0001] The invention belongs to the field of brain-like bionics, and more specifically relates to an adaptive neuron circuit based on a memristor. Background technique [0002] Simulating the physiological structure and working mechanism of the human brain to construct a bionic neural computing system is an important way to realize artificial intelligence. The human brain is composed of about 10 billion neurons and about 10 billion synapses, in which a single neuron is interconnected with multiple protrusions to form a complex network structure. Therefore, the premise of simulating the structure of the human brain is that the hardware implements neurons and synapses. There are two basic units of the synapse. Traditional artificial neurons and artificial synapses are constructed based on CMOS circuits. Dozens or even hundreds of transistors are often required to realize a single neuron or synapse. The circuit structure is complicated, the area is large, and t...

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 memristor-based adaptive neuron circuit, which aims to solve the problem that the prior art cannot simulate the ability of neurons to adapt to constant stimulation

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