A Self-Adaptive Frequency Decomposition Approach for Denoising to Enhance Data-Driven Learning of Cyclic Time Series in Medical Signal Estimation

A Self-Adaptive Frequency Decomposition Approach for Denoising to Enhance Data-Driven Learning of Cyclic Time Series in Medical Signal Estimation

In recent advancements within the data-driven world, cyclic time series have become indispensable in industries such as healthcare, manufacturing, and energy. Deep learning methodologies have significantly improved predictions for cyclic time series across these domains. This study investigates the...

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Bibliographic Details
Main Authors: Shang-Wei Chao, Feng-Li Lian
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Adaptive frequency band decomposition
photoplethysmography
prediction algorithms
sensor systems
signal denoising
time series analysis
Online Access:https://ieeexplore.ieee.org/document/10820351/
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https://ieeexplore.ieee.org/document/10820351/

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