MATLAB Program for Calculating Delay Time and Embedding Dimension Using CC Method
A MATLAB implementation employing the CC method to compute time delay and embedding dimension parameters for time series analysis
Explore MATLAB source code curated for "matlab程序" with clean implementations, documentation, and examples.
A MATLAB implementation employing the CC method to compute time delay and embedding dimension parameters for time series analysis
This interesting MATLAB program generates a beautiful canon musical piece through algorithmic composition. The implementation likely involves audio synthesis using MATLAB's Signal Processing Toolbox functions like audioplayer and soundsc, with potential use of trigonometric functions for waveform generation.
MATLAB implementation package for solving differential equations using finite difference discretization and Gauss-Seidel iterative solver (matlab_finite_difference_gauss_seidel.rar)
MATLAB program for calculating correlation dimension - (MEX function, ultra-fast)-----------------------------------Directory contents: 1. CorrelationDimension_main.m - Main program file 2. LorenzData.dll - Generates Lorenz discrete data 3. normalize_1.m - Data normalization 4. PhaSpaRecon.m - Phase space reconstruction 5. CorrelationDimension.dll - Correlation integral calculation function 6. CorrDim_buffer.dll - Cache file
Several MATLAB programs for calculating Leaf Area Index (LAI) with detailed descriptions included. Contains three specialized mini-programs with code implementation features.
Implementation of both scale-free and small-world network models using MATLAB programming, including algorithm descriptions and key function explanations
A MATLAB implementation for triangular mesh generation utilizing linear interpolation algorithms, featuring command-line operation and customizable data input for scientific visualization.
MATLAB code implementation and practical application examples of KSVD algorithm for reference and learning purposes.
A comprehensive MATLAB implementation of active contour models with customizable parameters and interactive visualization capabilities.
A concise MATLAB implementation of 2DPCA (Two-Dimensional Principal Component Analysis) designed for academic projects. Unlike some complex foreign implementations, this version focuses on clarity and practicality. The code includes proper matrix operations for covariance calculation and eigenvalue decomposition, ensuring correctness through rigorous testing. Suitable for beginners learning pattern recognition and experienced users needing a reliable 2DPCA baseline.