MATLAB Source Code for ISODATA Algorithm in Pattern Recognition

This repository contains MATLAB source code implementing the ISODATA (Iterative Self-Organizing Data Analysis Techniques Algorithm) for pattern recognition tasks. The code comprehensively demonstrates the algorithm's core workflow through modular implementation covering key stages: data preprocessing and initialization, dynamic cluster center selection using statistical thresholds, iterative cluster assignment based on minimum distance criteria, and cluster merging/splitting operations with automated parameter control. The implementation includes detailed inline comments explaining the mathematical background, algorithm flow control, and MATLAB-specific programming techniques such as vectorization for efficient distance calculations and cluster operations. Researchers and students can study this code to understand both the theoretical foundations and practical implementation considerations of this classic clustering algorithm in a MATLAB environment.