Power Spectrum Estimation of Random Signals Using Autocorrelation Function and Periodogram Methods

Implementation of power spectrum estimation for random signals through autocorrelation function and periodogram methods, with analysis of how data length, autocorrelation sequence length, signal-to-noise ratio, window functions, and averaging次数 affect spectral resolution, stability, main lobe width, and side lobe effects. Includes code implementation considerations for parameter optimization.