Power Spectral Density Estimation of Signals

Implementing power spectral density estimation using both autocorrelation function method and periodogram approach with MATLAB code examples

Autocorrelation Method for Pitch Detection

MATLAB implementation of autocorrelation-based pitch detection algorithm. This method employs fast autocorrelation function computation to detect speech pitch frequency, effectively eliminating interference from high-frequency formants and noise. The algorithm provides high estimation accuracy, excellent stability, and rapid computational performance through efficient peak detection and signal windowing techniques.

Implementation of Random Signal Spectral Analysis Techniques

Implementation of spectral analysis techniques for random signals, including spectral estimation and quality assessment. Methods for estimating power spectral density of system responses when discrete random signals pass through linear time-invariant systems: Autocorrelation Function Method, Periodogram Method, Bartlett's Method, Welch's Method, Multitaper Method (MTM), and Multiple Signal Classification (MUSIC) Method.

Calculating Time Delay t and Embedding Dimension m

This program calculates both time delay t and embedding dimension m simultaneously, offering a more efficient alternative to conventional autocorrelation function and GP methods. The algorithm is particularly useful for Lyapunov exponent computation where both parameters need to be determined beforehand. The implementation involves phase space reconstruction techniques and mutual information optimization for optimal parameter selection.