Explore MATLAB source code curated for "时间延迟" with clean implementations, documentation, and examples.
Implementation of C-C method algorithms for computing optimal time delay and embedding dimension, with applications in Lyapunov exponent calculation, correlation dimension analysis, and chaotic time series prediction. Includes MATLAB/Python code insights for signal processing and nonlinear dynamics.
Calculating the embedding dimension of Rossler system by combining time delay obtained through mutual information method with Cao's approach, including implementation details for phase space reconstruction.
Implementation of the modified CC method for calculating time delay and embedding dimension with enhanced performance and control
CC_method: A MATLAB implementation of the C-C method for phase space reconstruction in nonlinear time series analysis, calculating optimal time delay (tau) and time window (tw). This code was successfully implemented on MATLAB 7.0 on December 1, 2008, generating 5 key parameters and graphical outputs with excellent results. Includes subroutines for: 1) Lorenz system validation, 2) tau/tw calculation, 3) time series decomposition, 4) phase space reconstruction, and 5) correlation integral computation.
Implementation of mutual information method for calculating time delay in chaotic equations analysis using MATLAB with comprehensive code descriptions
This program implements the autocorrelation method to calculate the optimal time delay parameter for reconstructing chaotic time series from observed data.
MATLAB Nonlinear Chaotic Analysis Toolbox: Comprehensive implementation for time delay estimation, embedding dimension calculation, maximum Lyapunov exponent determination, correlation dimension analysis, and entropy computation. Eliminates the need for custom programming with built-in functions for chaotic time series analysis.
MATLAB implementation for strapdown inertial navigation system transfer alignment with tracking and time delay compensation
Implementing the C-C Method from Chaos Toolbox to Compute Time Delay and Embedding Dimension for Accurate Chaotic Time Series Forecasting
Traditional time delay estimation methods typically rely on signal correlation techniques, whereas employing the MUSIC algorithm significantly enhances precision. This approach can be implemented using eigenvalue decomposition of the signal covariance matrix and peak detection in the pseudospectrum.