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Neural network space mapping method for large signal modeling of power transistor

A power transistor and neural network technology, applied in the field of neural network space mapping, can solve problems such as the unreported modeling method of neural network space mapping, and achieve the effect of wide application prospects

Pending Publication Date: 2020-11-20
TIANJIN CHENGJIAN UNIV
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Problems solved by technology

However, the neural network spatial mapping modeling method considering the room temperature effect and self-heating effect has not been reported

Method used

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  • Neural network space mapping method for large signal modeling of power transistor
  • Neural network space mapping method for large signal modeling of power transistor
  • Neural network space mapping method for large signal modeling of power transistor

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Embodiment Construction

[0048] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0049] Such as figure 1 As shown, the dynamic neural network spatial mapping electrothermal model consists of two parts: the electrothermal rough model and the dynamic mapping neural network. First, the external voltage v across the gate and drain of the power transistor to be modeled f1 , v f2 and room temperature T af respectively by the dynamic mapping neural network f ANN1 (), f ANN2 () and f ANN3 () Map it to the voltage v across the gate and drain of the electrothermal rough model c1 , v c2 and room temperature T ac . Second, the voltage excites v c1 and v c2 Loaded on both ends of the gate and drain of the electrothermal rough model, it can be obtained when the room temperature is T ac The current response at both ends of the gate and drain i c1 and i c2 . Finally, output the current at both ends of the gate and drain of th...

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Abstract

The invention discloses a neural network space mapping method for large signal modeling of a power transistor. The method can be used for establishing a large signal model of the power transistor which accurately considers a room temperature effect and a self-heating effect. The method comprises the steps of 1, selecting an electric heating rough model according to the type of a to-be-modeled power transistor; 2, initializing a dynamic mapping neural network; 3, respectively establishing a direct current simulation model, a small signal simulation model and a large signal simulation model of the dynamic neural network space mapping electric heating initial model; 4, obtaining a final weight w1 of the dynamic mapping neural network; step 5, establishing a dynamic mapping neural network in commercial circuit simulation software; and step 6, establishing a dynamic neural network space mapping electric heating model in commercial circuit simulation software. The method has the beneficial effects that the large-signal electric heating characteristics of the power transistor considering the room temperature effect and the self-heating effect are reflected more accurately; the method is embedded into commercial circuit simulation software for high-level microwave circuit and system simulation, design and optimization.

Description

technical field [0001] The invention relates to the field of microwave device and circuit modeling, in particular to a neural network space mapping method for power transistor large signal modeling. It is suitable for the application of neural network technology in the field of microwave transistor modeling. Background technique [0002] With the rapid development of technologies such as wireless communication and radar detection, modern electronic equipment has higher and higher requirements on the operating frequency and power density of microwave transistors. The power transistor has better high-frequency performance and higher power quality factor, which makes it play a very important role in high-frequency and high-power applications. At present, the characteristics of most microwave and radio frequency transistors are affected by temperature, especially for power devices. Its operating temperature seriously affects the reliability and electrical characteristics of th...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F30/27G06F30/30G06N3/04
CPCG06F30/27G06F30/30G06N3/049
Inventor 朱琳赵坚李梅庞毅袁文聪
Owner TIANJIN CHENGJIAN UNIV
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