Time Series Denoising

Time series denoising (Time Series Denoising) refers to the process of extracting useful signals from time series data containing noise through signal processing techniques. Its main objective is to reduce or eliminate random fluctuations and interference in the data, improve the signal-to-noise ratio, thereby enhancing the analyzability and predictive accuracy of the data. Time series denoising has significant application value in fields such as financial analysis, medical monitoring, and industrial control, effectively improving the performance and reliability of systems.