Computation of Fundamental Matrix for 3D Reconstruction
Implementation of Fundamental Matrix Operations for 3D Reconstruction in Computer Vision Using MATLAB
Explore MATLAB source code curated for "运算" with clean implementations, documentation, and examples.
Implementation of Fundamental Matrix Operations for 3D Reconstruction in Computer Vision Using MATLAB
Successfully implemented and tested a 1024-point FFT operation using MATLAB, achieving excellent runtime performance and accurate frequency domain analysis
Implementation program for wavelet neural networks with computational coding based on MATLAB operations, including algorithm explanations and key function descriptions
Implementation of PQ decomposition method for load flow analysis with three test cases included. Users can perform additional calculations by modifying the input data files. The implementation demonstrates how to structure power system data and apply iterative solving techniques.
A comprehensive and intuitive MATLAB simulation program for Reed-Solomon encoding and decoding, featuring modular GF(Q) arithmetic operations (each operation implemented as separate function files), RS encoding module, and a detailed decoding module. The decoding module includes submodules for syndrome calculation, error locator polynomial computation, error position determination, and error magnitude calculation. Includes dedicated testbench functionality for verifying each module's correctness with complete implementation details and algorithm explanations.
The MATLAB Mathematics Handbook Comprehensive Edition provides exhaustive coverage including: matrix operations and fundamental computations, eigenvalue and quadratic form numerical calculations with data analysis, interpolation, fitting and table lookup, numerical solutions for ordinary differential equations and partial differential equations, symbolic computation, integral transforms, Taylor series, probability and statistics, random number generation, probability density calculations for random variables, cumulative probability values (distribution function values) for random variables, frequency tables for positive integers, empirical cumulative distribution function plots, and least squares linear fitting. Additionally covers probability plotting for normal and Weibull distributions, box plots for sample data, adding reference lines to graphs, polynomial curve fitting to existing plots, sample probability plots, and histograms with superimposed normal density curves.
MATLAB quaternion class implementation featuring essential quaternion operations and rotation applications
Part 1: Numerical Arrays and Their Operations - Implementation Approaches and Applications
A comprehensive MATLAB toolbox supporting quaternion (Hamilton numbers) computations with optimized functions for 3D rotations and spatial transformations