Explore MATLAB source code curated for "图论" with clean implementations, documentation, and examples.
Comprehensive MATLAB implementations for essential graph theory algorithms: Warshall-Floyd algorithm for shortest paths in weighted graphs, Kruskal's algorithm for minimum spanning trees, Hungarian algorithm for bipartite graph matching, feasible labeling method for optimal matching, and Ford-Fulkerson labeling algorithm for maximum flow computation. Complete with detailed code explanations and implementation approaches.
MATLAB implementations of graph theory algorithms including: Dijkstra's shortest path algorithm using set commands, Floyd-Warshall algorithm for all-pairs shortest paths, Hungarian algorithm (Hungary) for maximum bipartite matching, two methods for minimum spanning tree algorithms, and minimum-cost maximum-flow algorithm.
A MATLAB program for wireless sensor network (WSN) energy consumption simulation using graph theory packet forwarding algorithms. This implementation models energy-efficient routing protocols, calculates transmission costs, and analyzes network lifetime optimization through adjacency matrices, shortest path algorithms, and energy dissipation models.
Spectrum Allocation Algorithm in Cognitive Radio Networks: Graph Theory-Based Color-Sensitive Algorithm Implementation
Implementation of Kruskal's algorithm for Minimum Spanning Tree in graph theory with visualization program. M-function format [Wt, Pp] = mintreek(n, W) where n represents number of graph vertices, W is weighted adjacency matrix (non-connected vertices use 'inf'). Displays MST edges/vertices: Wt stores total weight, Pp(:,1:2) contains edge vertices, Pp(:,3) edge weights, Pp(:,4) edge indices. Red lines in plot indicate MST connections.
The random walker algorithm, initially proposed by Leo Grady and Gareth Funka-Lea, is a graph-based segmentation technique that models image pixels as nodes in a graph and computes electrical potentials to achieve multi-label segmentation. This method formulates segmentation as a combinatorial Dirichlet problem solvable through sparse linear systems, making it particularly effective for medical imaging applications with weak boundaries and noise.
MEX implementation of Dijkstra's shortest path algorithm for graph theory applications, featuring efficient pathfinding in weighted graphs with C++ performance optimization.
The Depth-First Search algorithm, frequently utilized in graph theory, is commonly applied in reliability islanding computations for power systems with key applications in network traversal and pathfinding scenarios.
MATLAB Implementation for Maximum Flow Problem in Graph Theory This MATLAB code demonstrates the solution to the maximum flow problem using the Ford-Fulkerson algorithm, which calculates the optimal flow capacity for a given network graph.
A comprehensive graph theory toolbox containing implemented algorithms and documentation for solving critical problems including shortest path algorithms (Dijkstra, Bellman-Ford), spanning tree constructions (Prim, Kruskal), and related graph optimization challenges with practical code examples and applications.