The Well-Known Bispectrum
The well-known bispectrum, which represents third-order spectral estimation, holds significant reference value in cosmological research.
Additive Gaussian Noise Removal from Signals Using Bispectral and Wavelet Transform Methods
This set of programs implements additive Gaussian noise removal through bispectral analysis and wavelet transforms. Key implementations include: 1. Bispectral analysis program for single variables calculating third-order cumulants and Fourier transforms 2. Autocorrelation function computation using inverse Fourier transform with proper normalization 3. Spectral analysis suite using FFT for preference spectrum, power spectrum, RMS spectrum, and logarithmic spectrum 4. Wavelet-based denoising pipeline for .wav audio signals with white noise removal 5. Comparative analysis framework evaluating multiple wavelet types and thresholding techniques on identical signals
Higher-Order Spectra (Including Bispectrum) Analysis in MATLAB
MATLAB implementation of higher-order spectra analysis including bispectrum, featuring both direct and indirect methods for signal detection and time-delay estimation with enhanced algorithm descriptions.
Computation of Three-Dimensional and Two-Dimensional Biphase Spectrum Plots for Time Series Analysis
Calculate and visualize time series biphase spectrum using 3D and 2D plots, essential for investigating nonlinear processes with code-driven implementation techniques