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Alex Blank
2025-03-14 13:51:47 +01:00
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thesis/sections/background.tex
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@@ -84,4 +84,12 @@ detecting the slight temperature rise that follows ovulation.
Advances in wearable technology have further enabled continuous and automated temperature monitoring,
improving accessibility and usability\cite{alexander_fertilitatsmonitoring_2014, luo_detection_2020, yu_tracking_2022}.
\subsection{Technical Background}\label{subsec:technological_background}
\subsection{Technical Background}\label{subsec:technological_background}
\subsubsection{Time Series Analysis}\label{subsubsec:time_series_analysis}
Time series analysis is a fundamental tool for studying sequential data that evolves over time.
Unlike other data types, time series data has an inherent temporal order, where each data point is associated
with a timestamp, capturing its dependence on past values.
The goal of time series analysis is to model these dependencies and extract meaningful insights.
While related to signal processing, time series analysis focuses more on long-term trends and forecasting,
rather than frequency-domain characteristics.
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