Power Spectrum Estimation Using Burg Algorithm

This paper employs the Burg algorithm for power spectrum estimation. The implementation allows for parameter adjustments including signal-to-noise ratio (SNR) and model order P to control spectral resolution for analytical purposes. The algorithm implementation typically involves key functions such as burg() for coefficient calculation and pburg() for spectrum estimation in signal processing environments. Through iterative reflection coefficient computation and forward-backward prediction error minimization, the method provides high-resolution spectral estimates. Additionally, this approach enables the study of signal spectral characteristics and peak localization. Spectral analysis through this method facilitates better understanding of signal features and properties, with practical applications in identifying dominant frequency components and spectral patterns. The code implementation may include visualization functions to display spectral peaks and compare results under different parameter settings.