Academic Journal
48‐3: Distinguished Student Paper: AI‐Algorithm‐Driven Automated Layout Generation Method for Flat Panel Display with High Aperture‐Ratio and Charging‐Ratio.
| Τίτλος: | 48‐3: Distinguished Student Paper: AI‐Algorithm‐Driven Automated Layout Generation Method for Flat Panel Display with High Aperture‐Ratio and Charging‐Ratio. |
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| Συγγραφείς: | Tang, Haodong, Zeng, Haohang, Yuan, Weiming, Qiu, Zhiren, Zou, Lanrong, Liao, Congwei, Zhang, Shengdong |
| Πηγή: | SID Symposium Digest of Technical Papers; Aug2026 Supplement 1, Vol. 57, p478-481, 4p |
| Θεματικοί όροι: | Flat panel displays, Deep learning, Optical apertures, Software libraries (Computer programming), Simulation Program with Integrated Circuit Emphasis |
| Περίληψη: | This paper presents an AI‐driven layout automated generation method for flat panel displays (FPDs) layouts. By using PyAether's Python API to design code, this work automates layout generation, RC extraction, SPICE simulation, and optimizations. Pixel parameters of width and length of TFT, and the geometric shapes of gateline and dataline are automatically optimized within 36 seconds. Furthermore, deep learning algorithms, including sequential quadratic programming (SQP), simulated annealing (SA), and artificial neural networks (ANNs) optimization were used to improve the charging ratio. The proposed method obtains a 13.02% aperture ratio improvement while ensuring ≥90% charging ratio. [ABSTRACT FROM AUTHOR] |
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| Βάση Δεδομένων: | Complementary Index |
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