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• W4387005334 abstract "Peak detection (PD) is a valuable technique in time series analysis that can be employed to identify significant local maxima or minima within the time series. Peaks are significant points in a signal or spectrum that are of interest, as they can represent important features in various applications such as chromatography, spectroscopy, biomedical signal processing, and image analysis, to name a few. However, due to the unpredictable and fluctuating nature of many real-time sources, current peak detection algorithms usually fail to detect stable peaks across varied real-time time series. Furthermore, they experience a dip in performance when trying to develop a general algorithm applicable across various application areas. To address this challenge, we have developed a novel and robust online two-stage peak detection algorithm (TSPD). Our TSPD algorithm can adapt to a wide range of application areas by adjusting only two tunable parameters in its computational process. To demonstrate the efficacy of our algorithm, we conducted experiments using seven real-world datasets and demonstrated the improved performance of the TSPD algorithm over other notable existing techniques." @default.
• W4387005334 created "2023-09-26" @default.
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• W4387005334 date "2023-07-01" @default.
• W4387005334 modified "2023-09-26" @default.
• W4387005334 title "TSPD: A Robust Online Time Series Two-Stage Peak Detection Algorithm" @default.
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• W4387005334 doi "https://doi.org/10.1109/sose58276.2023.00017" @default.
• W4387005334 hasPublicationYear "2023" @default.
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