P‐14: a‐IGZO TFT Based Pixel Circuits for AM‐OLED Displays

Jung, Hyunseung; Kim, Yongchan; Kim, Young-Seok; Chen, Charlene; Kanicki, Jerzy; Lee, Ho-Jin

doi:10.1002/j.2168-0159.2012.tb05983.x

Cited by 7 publications

(3 citation statements)

References 9 publications

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“…6 is the deviation percentage of the currents at V TH = 7 ± 1 V from the OLED current at V TH = 7 V. The OLED current error rate in the proposed pixel circuit was suppressed to less than 3% for ㅿV TH = ± 1 V of the drive TFT. This is an improved error rate compared to the previous circuit, which showed an error rate of 20 % [23]. The OLED current error rate was defined using the following equation: Fig.…”

Section: Resultsmentioning

confidence: 99%

Pixel Circuit with Threshold Voltage Compensation using a-IGZO TFT for AMOLED

Lee¹,

Hwang²,

Bae³

2014

JSTS:Journal of Semiconductor Technology and Science

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Abstract-A threshold voltage compensation pixel circuit was developed for active-matrix organic light emitting diodes (AMOLEDs) using amorphous indium-gallium-zinc-oxide thin-film transistors (a-IGZO-TFTs). Oxide TFTs are n-channel TFTs; therefore, we developed a circuit for the n-channel TFT characteristics. The proposed pixel circuit was verified and proved by circuit analysis and circuit simulations. The proposed circuit was able to compensate for the threshold voltage variations of the drive TFT in AMOLEDs. The error rate of the OLED current for a threshold voltage change of 3 V was as low as 1.5%.

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Section: Resultsmentioning

confidence: 99%

Pixel Circuit with Threshold Voltage Compensation using a-IGZO TFT for AMOLED

Lee¹,

Hwang²,

Bae³

2014

JSTS:Journal of Semiconductor Technology and Science

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“…The second is organic light-emitting diodes (OLEDs), which generate an image by controlling the amount of current supplied to the OLED device. OLED displays have significant advantages, such as high color-reproduction ranges, low power consumption, high brightness, high contrast ratio, and a wide viewing angle [ 1 , 2 , 3 ]. However, despite their excellent performance, they are hindered by the burn-in phenomenon that is caused by the operating mechanism of OLED displays.…”

Section: Introductionmentioning

confidence: 99%

Luminance-Degradation Compensation Based on Multistream Self-Attention to Address Thin-Film Transistor-Organic Light Emitting Diode Burn-In

Park

Chang

2021

Sensors

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We propose a deep-learning algorithm that directly compensates for luminance degradation because of the deterioration of organic light-emitting diode (OLED) devices to address the burn-in phenomenon of OLED displays. Conventional compensation circuits are encumbered by high cost of the development and manufacturing processes because of their complexity. However, given that deep-learning algorithms are typically mounted onto systems on chip (SoC), the complexity of the circuit design is reduced, and the circuit can be reused by only relearning the changed characteristics of the new pixel device. The proposed approach comprises deep-feature generation and multistream self-attention, which decipher the importance of the variables, and the correlation between burn-in-related variables. It also utilizes a deep neural network that identifies the nonlinear relationship between extracted features and luminance degradation. Thereafter, luminance degradation is estimated from burn-in-related variables, and the burn-in phenomenon can be addressed by compensating for luminance degradation. Experiment results revealed that compensation was successfully achieved within an error range of 4.56%, and demonstrated the potential of a new approach that could mitigate the burn-in phenomenon by directly compensating for pixel-level luminance deviation.

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“…The second is an organic light emitting diode (OLED), which generates an image by controlling the amount of current supplied to the OLED device. OLED displays have significant advantages such as high color reproduction ranges, low power consumption, high brightness, high contrast ratio and wide viewing angle [1][2][3]. However, despite their excellent performance, they are hindered by the burn-in phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Luminance Degradation Compensation Based on Multi-Stream Self-Attention to Address Thin Film Transistor-Organic Light Emitting Diode Burn-in

Park¹,

Park²,

Chang³

2021

Preprint

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In this study, we propose a deep learning algorithm that directly compensates for luminance degradation owing to the deterioration of organic light emitting diode (OLED) devices to address the burn-in phenomenon of OLED displays. Conventional compensation circuits are encumbered by a high cost of development and manufacturing processes owing to their complexity. However, given that deep learning algorithms are typically mounted on a system on chip (SoC), the complexity of the circuit design is reduced, and the circuit can be reused by re-learning only the changed characteristics of the new pixel device. The proposed approach comprises deep feature generation and multi-stream self-attention, which decipher the importance of the variables, and the correlation between burn-in-related variables. It also utilizes a deep neural network that identifies the nonlinear relationship between the extracted features and luminance degradation. Thereafter, the luminance degradation is estimated from the burn-in-related variables, and the burn-in phenomenon can be addressed by compensating for the luminance degradation. The experimental results revealed that compensation was successfully achieved within an error range of 2.69%, and demonstrate the potential of a new approach that can mitigate the burn-in phenomenon by directly compensating for pixel-level luminance deviation.

show abstract

P‐14: a‐IGZO TFT Based Pixel Circuits for AM‐OLED Displays

Cited by 7 publications

References 9 publications

Pixel Circuit with Threshold Voltage Compensation using a-IGZO TFT for AMOLED

Pixel Circuit with Threshold Voltage Compensation using a-IGZO TFT for AMOLED

Luminance-Degradation Compensation Based on Multistream Self-Attention to Address Thin-Film Transistor-Organic Light Emitting Diode Burn-In

Luminance Degradation Compensation Based on Multi-Stream Self-Attention to Address Thin Film Transistor-Organic Light Emitting Diode Burn-in

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