A Collection of Classical Graph Theory Algorithms
This compressed archive contains a comprehensive collection of classical graph theory algorithms primarily developed in MATLAB, offering a complete variety suitable for learning purposes.
Collection of Various Beamforming Methods
A comprehensive collection of various beamforming methods, highly practical and user-friendly, though not original implementations. Includes algorithm explanations and code implementation references.
Set-Based Discrete Particle Swarm Optimization Algorithm
Implementation of a set-based discrete particle swarm optimization algorithm with customizable parameters for immediate execution. Key variables include: global popsize (population size), global pop (population matrix), global c1 (cognitive coefficient), global c2 (social coefficient), global gbest_x (global best x-coordinate), and global gbest (global best solution). The algorithm requires proper parameter initialization for optimal performance.