Power Spectrum Estimation with MATLAB Implementation
MATLAB routines for power spectrum estimation with algorithm explanations
MATLAB Simulation of Power Spectrum Estimation Using MUSIC Method
MATLAB simulation of power spectrum estimation based on MUSIC algorithm, including detailed experimental report, complete source code, runtime results, and comprehensive analysis with implementation insights.
Power Spectrum Estimation Using Burg Algorithm
Implementation of power spectrum estimation using Burg algorithm with adjustable signal-to-noise ratio (SNR), model order P, and resolution analysis capabilities
MATLAB Code Implementation of ARIMA Model
ARIMA Model for Power Spectrum Estimation of Non-Stationary Signals, Including Implementation Approaches and Key Functions
Linear Modeling of AR Processes and Power Spectrum Estimation: Yule-Walker, Covariance, Burg, and Modified Covariance Methods
Implementation approaches for AR process modeling and power spectrum estimation using: (1) Yule-Walker method (autocorrelation approach); (2) Covariance method; (3) Burg method; (4) Modified covariance method
Wavelet Transform-Based Power Spectrum Estimation
MATLAB simulation code for power spectrum estimation using wavelet transform, featuring fundamental wavelet transform implementation, Mallat algorithm realization, and comparative simulations between classical and modern power spectrum estimation methods.
Correlation Function Method
The correlation function method estimates the autocorrelation function R from sequences, then applies Fourier transform to obtain power spectrum estimation. This approach provides strong estimation accuracy when the time delay is relatively small compared to the data length. Implementation typically involves computing lagged products and applying FFT algorithms for efficient spectral analysis.
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.
Power Spectrum Estimation Implementation in MATLAB Environment
A MATLAB-based power spectrum estimation program utilizing classical methods with integrated plotting capabilities for signal analysis
MATLAB Code Implementation for Power Spectrum Estimation
Power spectrum estimation techniques including Periodogram method, Burg method, MUSIC method, and Welch method with comparative plotting and code implementation details