MATLAB Implementation of Scale-Free Network Generation

This article presents a MATLAB-based implementation for generating and analyzing scale-free networks. The program provides fundamental network manipulation capabilities including network generation algorithms, node addition/removal functions, and graph visualization tools. Through this implementation, users will gain practical understanding of scale-free network properties and learn MATLAB techniques for network data processing. The program implements the Barabási-Albert model algorithm which starts with a small connected network and preferentially attaches new nodes to existing highly-connected nodes. Key MATLAB functions include: - graph() for creating network structures - addedge() and rmnode() for dynamic network modifications - plot() with layout customization for visualization - degree() calculation for analyzing connectivity distributions Users can modify parameters like initial network size, attachment probability, and growth rate to study different scale-free network characteristics. The implementation demonstrates how to handle adjacency matrices, calculate node degrees, and visualize complex networks using MATLAB's graphing capabilities. This practical tool serves as both an educational resource for understanding scale-free networks and a foundation for more advanced network research applications.