Solving Partial Differential Equations with MATLAB
Comprehensive MATLAB guide for solving PDEs with extensive practical examples and code implementations
Explore MATLAB source code curated for "Matlab" with clean implementations, documentation, and examples.
Comprehensive MATLAB guide for solving PDEs with extensive practical examples and code implementations
MATLAB-based optical simulation platform modeling Young's double-slit interference, equal-inclination and equal-thickness interference, and arbitrary multi-beam interference. Features an interactive GUI for parameter adjustment and real-time visualization, with extensible architecture for complex interference phenomena simulation.
MATLAB source code for computing generalized fractal dimensions with function signature: function [dq, rq] = fdim(q, x, trace). This implementation calculates different fractal dimension definitions based on q-values: q=0 for Hausdorff dimension, q=1 for Information dimension, q=2 for Correlation dimension, etc. The algorithm employs box-counting methods with logarithmic scaling analysis for dimension estimation.
MATLAB-based LK optical flow algorithm with Gaussian pyramid implementation, ready to run with included standard reference images for performance validation.
MATLAB-based conversion between spatial Cartesian coordinates and geodetic coordinates with mathematical algorithm implementation and parameter configuration
This MATLAB implementation utilizes the transfer matrix method to calculate photonic crystal reflectance, featuring program code in a Word document with accompanying MATLAB-generated plots that demonstrate practical applications and computational results.
Wind turbine blade design based on Wilson's method, utilizing MATLAB's fmincon function to solve axial and tangential induction factors for optimal blade performance
This collection features 18 fully debugged MATLAB cellular automata source codes, covering fundamental algorithms like Conway's Game of Life and traffic flow simulations. Includes implementations of key functions such as neighborhood evaluation and state transition rules, serving as essential reference material for researchers studying cellular automata in MATLAB environments.
This MATLAB program implements algorithms to compute the minimum bounding rectangle and maximum inscribed rectangle for irregular shapes. The implementation includes sample shape files for immediate execution and experimental validation, featuring optimized computational geometry approaches.
This MATLAB implementation of Support Vector Machine (SVM) provides a functional codebase for classification tasks, featuring data preprocessing, kernel selection, model training, and prediction capabilities.