MATLAB Implementation of Complex Network BA Model

Complex Networks refer to networks composed of large numbers of nodes and interconnections. The Barabási-Albert (BA) model can be implemented in MATLAB to simulate such networks through parameter adjustments, generating various simulation graphs. The core algorithm involves preferential attachment where new nodes connect to existing ones with probability proportional to their degree. Key implementation functions include network initialization, node addition loops, and degree distribution calculations. Parameter variables typically control network size (number of nodes), initial connections, and attachment preferences. Beyond simulations, complex networks have extensive real-world applications including social networks, internet infrastructure, protein-protein interaction networks, making their study academically and practically significant. The MATLAB code typically outputs degree distribution plots, network connectivity graphs, and scalability analyses through visualization functions like plot() and hist().