MATLAB Wave Superposition Algorithm for Seismic Data Processing
MATLAB source code for wave superposition implementation, originally sourced from the internet. This program demonstrates key seismic data processing techniques.
Explore MATLAB source code curated for "Matlab" with clean implementations, documentation, and examples.
MATLAB source code for wave superposition implementation, originally sourced from the internet. This program demonstrates key seismic data processing techniques.
Complete MATLAB program implementing various rough set attribute reduction techniques including positive region approximation, entropy-based methods, and genetic algorithm approaches with full code implementation and detailed explanations.
Comprehensive MATLAB implementation of five distinct matrix inversion algorithms with detailed documentation and code explanations
The implementation of kd-tree in MATLAB primarily consists of 4 core subfunctions
MATLAB implementation for computing membership degrees in fuzzy relations with graphical visualization capabilities, including color-coded representations and various fuzzy logic methodologies.
MATLAB implementation of sub-pixel translation registration achieving 0.03-pixel precision with image preprocessing and advanced interpolation algorithms
MATLAB-based simple quadcopter model suitable for flight simulation, featuring dynamic parameter adjustment and flight characteristic analysis
Verified MATLAB source code for chi-square test implementation, thoroughly tested and functional!
This MATLAB program creates Voronoi diagrams while generating random seed points constrained by specific distance relationships. It outputs both seed point coordinates and corresponding vertex coordinates for ABAQUS modeling implementation. The algorithm ensures proper Voronoi tessellation through Delaunay triangulation and geometric constraints validation.
This internationally sourced MATLAB toolbox efficiently computes mutual information and entropy for random variables, featuring probabilistic distribution functions, stochastic process modeling, and signal processing applications with comprehensive documentation.