학술논문

Learning-based Denoising Algorithm for the Reconstructed Image using Electromagnetic Emanations from the Display Device
Document Type
Conference
Source
2022 IEEE International Symposium on Electromagnetic Compatibility & Signal/Power Integrity (EMCSI) Electromagnetic Compatibility & Signal/Power Integrity (EMCSI), 2022 IEEE International Symposium on. :268-271 Aug, 2022
Subject
Aerospace
Components, Circuits, Devices and Systems
Fields, Waves and Electromagnetics
Power, Energy and Industry Applications
Noise reduction
Neural networks
Transforms
Interference
Robustness
Electromagnetics
Image reconstruction
EMI
Deep-learning
Convolutional neural network (CNN)
Wavelet transform
Language
Abstract
This paper proposes a learning-based denoising algorithm that improves the signal-to-noise ratio (SNR) of the information signal emitted from the display device. The information signal is easily degraded by noise and interference on the channel and has various SNR. In this situation, an algorithm that enhances the model's robustness is required to improve the degraded information signal into a learning-based denoising model. Therefore, this paper proposes a normalization method to enhance the robustness of the model.