Explore MATLAB source code curated for "功率谱估计" with clean implementations, documentation, and examples.
Modeling of AR random processes, given an AR process model, with power spectrum estimation using both Yule-Walker equations and covariance methods, including algorithm implementation considerations and key computational functions
Power spectrum estimation has broad applications across various disciplines and application domains, receiving significant attention. In the "Modern Signal Processing" course, we studied two primary spectral estimation methods: classical spectral estimation and modern spectral estimation. Classical spectral estimation, based on Fourier transform, offers high computational efficiency but suffers from low spectral resolution and severe side lobe leakage, making it suitable for long sequences. To overcome these limitations, researchers developed modern spectral estimation methods based on parametric models of stochastic processes, including maximum likelihood estimation, maximum entropy method, AR model approach, and predictive filtering techniques. Modern spectral estimation provides higher accuracy for short sequences, complementing classical methods. After thorough study, I selected modern spectral estimation for implementation, particularly focusing on AR model parameter estimation using techniques like the Yule-Walker equations or Burg's algorithm for efficient computation.
Implementing power spectral density estimation using both autocorrelation function method and periodogram approach with MATLAB code examples
MATLAB implementations for AR power spectrum estimation and ARMA power spectrum estimation with enhanced code-related descriptions.
This repository contains six folders featuring implementations of AR model using Burg's algorithm, power spectral estimation, Wiener filtering, AR model all-pole modeling, and related signal processing techniques with MATLAB/Python code examples.
MATLAB Power Spectrum Estimation of Pulsating Wind Speed Time History Using Hanning Window Method
Course project implementing Levinson algorithm for power spectrum estimation, including detailed experimental documentation with code analysis and performance evaluation.
MATLAB simulation program for power spectrum estimation. Starting from the fundamental principles of power spectrum estimation, this guide analyzes classical and modern spectral estimation methods, their characteristics, and MATLAB implementation approaches. Detailed coverage includes periodogram techniques and AR parameter methods with practical code examples.
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.
This document demonstrates power spectrum estimation implementation in MATLAB using higher-order cumulants method, providing code examples for signal frequency analysis and energy distribution computation.