MATLAB Implementation of Power Spectrum Estimation for Sunspot Analysis

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Resource Overview

This MATLAB-based power spectrum estimation project processes 100 years of sunspot activity data using periodogram, maximum entropy estimation (AR method and Burg method). The implementation generates signal power spectra to calculate sunspot activity cycles, featuring algorithm comparisons and spectral analysis techniques.

Detailed Documentation

This article presents a MATLAB implementation of power spectrum estimation algorithms. The input dataset consists of 100-year historical records of sunspot activity. Our implementation employs three spectral estimation techniques: the periodogram method for non-parametric analysis, and maximum entropy estimation through both Autoregressive (AR) modeling and Burg's algorithm for parametric approaches. The code generates power spectral density plots using MATLAB's signal processing toolbox functions, particularly periodogram() for direct spectral estimation, aryule() for AR parameter estimation, and pburg() for Burg's method implementation. By analyzing the resulting power spectra, we identify dominant frequency components corresponding to sunspot activity cycles. The implementation further calculates additional solar parameters including cycle duration and amplitude characteristics through peak detection algorithms and spectral integration methods.

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