Neural Network Correction Circuit for Display Image Discontinuity
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Solution Overview
Problem
Current semiconductor devices and display systems face challenges in achieving high-quality, high-resolution image display with low power consumption and high-speed operation, particularly due to issues with image discontinuity at boundaries between regions in high-resolution pixel arrays.
Innovation Solution
A display system incorporating a neural network-based correction circuit that compensates for image discontinuity by learning to correct image signals, using a hierarchical neural network structure and autoencoder architecture, with transistors featuring hydrogenated amorphous silicon or metal oxides in channel formation regions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the screen resolution is increased to achieve higher image quality, then the manufacturing precision and signal processing complexity increase, but the power consumption increases and image discontinuity at boundaries occurs
Solution Approach 1:
The pixel array is divided into multiple regions with different drive circuits, allowing independent optimization of each region's power consumption and signal processing requirements
Solution Approach 2:
The drive circuits adjust signal parameters dynamically based on pixel position, particularly modifying signal characteristics near region boundaries to prevent discontinuity while maintaining high resolution
2Measurement precision
If the screen resolution is increased to achieve higher image quality, then the manufacturing precision and signal processing complexity increase, but the operational speed decreases due to increased processing complexity
Solution Approach 1:
The pixel array is divided into multiple regions with different drive circuits, allowing parallel processing of different image regions which maintains operational speed while achieving high resolution
Solution Approach 2:
Boundary correction parameters are pre-calculated and stored in memory, allowing the drive circuits to quickly apply corrections without real-time computation delays
3Measurement precision
If the screen resolution is increased to achieve higher image quality, then the manufacturing precision increases, but image discontinuity occurs at boundaries between regions
Solution Approach 1:
Different drive circuits are designed with specialized characteristics optimized for their specific region, with boundary circuits incorporating correction functionality to maintain image continuity across region transitions
Solution Approach 2:
The system incorporates feedback mechanisms where boundary correction parameters are adjusted based on detected image discontinuity, automatically optimizing boundary transition smoothness
4Adaptability or versatility
If multiple drive circuits are used to manage high-resolution pixel arrays, then the device complexity increases, but the signal processing can be optimized for different regions
Solution Approach 1:
Multiple drive circuits are designed with standardized interfaces and similar functional capabilities, allowing them to be controlled uniformly while maintaining region-specific optimization, thereby reducing overall system complexity
Data Source
AI summary
A novel semiconductor device or display system is provided. The display system includes a correction circuit having a function of correcting an image signal by utilizing artificial intelligence. Specifically, learning by an artificial neural network enables the correction circuit to correct an image signal so as to alleviate the image discontinuity. Then, by making an inference (recognition) utilizing the artificial neural network which has finished the learning, the image signal is corrected and compensation for the image discontinuity can be made. In this manner, the junction can be inconspicuous on the displayed image, improving the quality of a high-resolution image.