A method for predicting the initial value of module gamma

Abstract

The invention discloses a method for predicting the initial value of Gamma of a module, which comprises the following steps: counting Gamma adjustment data of all binding points of a plurality of sample modules to obtain a standard characteristic curve suitable for all modules, and the standard characteristic curve is used for Characterize the mapping relationship between the characteristic quantities of all the binding points and the Gamma adjustment value; establish the first neural network model according to the standard characteristic curve; obtain the actual convergence of the Gamma adjustment value and the standard characteristic curve of one or more preset binding points of the module to be tested Obtain the difference value of the predicted Gamma adjustment value, and use the difference value to obtain a prediction model suitable for the module to be tested; use the prediction model to obtain the initial value of the Gamma adjustment of the binding point of the module to be tested, which can separate the screen and the screen. , and then obtain a more accurate screen-to-screen correction model.

Description

technical field [0001] The invention belongs to the field of module Gamma adjustment, in particular to a method for predicting the initial value of module Gamma. Background technique [0002] Organic Light-Emitting Diode (OLED) displays, also known as organic electroluminescent displays, play an important role in the display industry today. It is a different type of product from thin film transistor liquid crystal display (TFT-LCD), the former has the advantages of self-luminescence, wide viewing angle, high contrast, low power consumption, high response rate, full color and simple process. The basic structure of OLED is composed of a thin and transparent indium tin oxide (ITO) with semiconducting properties, which is connected to the positive electrode of electricity, plus another metal cathode, which is wrapped into a sandwich-like structure. When the electricity is supplied to an appropriate voltage , the positive hole and the negative charge will combine in the light-em...

AI Technical Summary

Problems solved by technology

The accuracy of the initial value prediction method depends on the understanding of the device characteristics of the screen and the establishment of a suitable physical model, but this physical model usually cannot describe the variation caused by the difficult-to-control variation of process and device parameters, including band-to- -band or screen-to-screen variation or batch-to-batch variation

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