BP neural network based GFET modeling method

A technology of BP neural network and modeling method, which is applied in the field of modeling of graphene field effect transistors, can solve the problems of long operation time, short calculation time, inability to apply circuit simulation tools, etc., and achieve the effect of fast calculation

Inactive Publication Date: 2015-09-16
WUHAN UNIV
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Problems solved by technology

[0003] Numerical calculations based on first principles or non-equilibrium Green's functions, numerical models can accurately simulate the characteristics of GFETs, but the calculation time is too long to be applied to circuit simulation tools
The intensive model uses analytical expressions to describe th...

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  • BP neural network based GFET modeling method
  • BP neural network based GFET modeling method
  • BP neural network based GFET modeling method

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[0052]In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.

[0053] A kind of GFET modeling method based on BP neural network provided by the invention comprises the following steps:

[0054] Step 1. Data collection: collect a certain amount of GFET input and output data for BP network model training and testing. The network model obtained after training and testing can be used to predict the performance of GFET under other input parameters. The input data includes the gate-source voltage V gs , drain-source voltage V ds , channel width W, channel length L, the output data is the channel current I d ; After the data...

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Abstract

The present invention discloses a BP neural network based GFET modeling method. The method comprises six steps of: collecting data; preprocessing the data; determining a BP network GFET model structure to be used; building and training a GFET model; performing denormalization on an output electric current predicted by the GFET model to obtain a model output value; and implementing Verilog-A of the GFET mode. The method of the present invention has the advantages of being short in calculation time, high in accuracy, requiring no complete theory knowledge of devices and being applicable to circuit design and simulation.

Description

technical field [0001] The invention belongs to the technical field of device modeling, in particular to a modeling method of a graphene field effect transistor (GFET). Background technique [0002] The device model is a tool to describe the performance of the device. To apply new devices to circuit design on a large scale, an accurate device model is essential. Traditional device models are mainly numerical models and intensive models. [0003] Based on first-principle or non-equilibrium Green's function numerical calculations, the numerical model can accurately simulate the characteristics of GFETs, but the calculation time is too long to be applied to circuit simulation tools. The intensive model uses analytical expressions to describe the characteristics of GFETs, and the calculation time is short. It can be integrated into circuit simulation tools for circuit design, but it requires a deep understanding of the working mechanism of GFETs and simplifies them into appropr...

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Application Information

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IPC IPC(8): G06F17/50G06N3/02
Inventor 常胜张济
Owner WUHAN UNIV
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