Pulse neuron circuit based on ferroelectric transistor

Abstract

The invention provides a pulse neuron circuit based on a ferroelectric transistor, and belongs to the technical field of pulse neuron in neural morphology calculation. The pulse neuron circuit comprises a ferroelectric transistor FeFET and a resistor, wherein a ferroelectric transistor L-FeFET is formed by enhancing polarization degradation characteristics of ferroelectric materials of the ferroelectric transistor FeFET, and the L-FeFET is used for simulating the accumulation and leakage characteristics of biological neurons, and a voltage pulse signal transmitted from a synapse is applied tothe gate of the L-FeFET; the source end of the L-FeFET is connected with the GND, and the drain end of the L-FeFET is connected to one end of the resistor; and the other end of the resistor is connected with a fixed power supply voltage, and the resistor is used for divides the voltage with the L-FeFET to generate a voltage pulse output of the neurons. Compared with an implementation mode based ona traditional MOSFET, the pulse neuron circuit has the advantages that the hardware expenditure can be obviously reduced, has strong driving capability, and is beneficial to hardware realization of alarge-scale highly interconnected pulse neural network.

Description

technical field [0001] The invention relates to the physical realization of pulse neurons in neuromorphic computing, in particular to a pulse neuron circuit based on ferroelectric transistors. Background technique [0002] With the vigorous development of information technology, human society has entered the era of "data explosion", and the annual exponential growth of data volume has brought unprecedented pressure on data processing and calculation. Due to the characteristics of the traditional von Neumann computing architecture, which separates storage and computing, the transmission of data between the storage unit and the computing unit will cause a lot of waste of power consumption and energy consumption. In today's information society and even the intelligent society, there is a huge amount of data In this context, this problem will become more and more serious. [0003] Inspired by the computing model of the human brain, the researchers proposed a neural network (Neu...

AI Technical Summary

Problems solved by technology

At present, in terms of the hardware implementation of neuromorphic computing, many research institutions and enterprises have developed a variety of neuromorphic chips. Mainly based on traditional CMOS circuit construction, the simulation of pulse neuron functions often relies on circuit modules composed of several MOSFET devices and capacitors, which has problems such as large hardware overhead and high circuit energy consumption, which is not conducive to high-density and large-scale integration. And may make the network lose the original power consumption and energy consumption advantages brought by the architecture level

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