Power Spectrum Analysis Algorithm

This document discusses the functionality of power spectrum analysis algorithms and relevant content from the reference book "Analysis of Meteorological Time Series" by Huang Jiayou. Power spectrum analysis algorithm is a method used to analyze signal frequency spectrum characteristics, helping researchers understand the frequency distribution of signals. In meteorological applications, this algorithm typically involves implementing Fast Fourier Transform (FFT) or Welch's method for spectral estimation, which helps identify dominant frequencies and periodic patterns in time series data. Huang Jiayou's book provides detailed explanations and practical application cases of power spectrum analysis algorithms, including MATLAB or Python code implementations for handling meteorological data. These contents serve as fundamental references for understanding the theoretical basis and practical implementation of power spectrum analysis algorithms, covering key aspects like windowing functions, spectral smoothing techniques, and significance testing for peak detection.