Implementation of Parzen Window Method, ISODATA Algorithm, and H-K (Ho-Kashyap) Algorithm in Pattern Recognition

This article provides a comprehensive exploration of three fundamental pattern recognition algorithms: the Parzen Window method, ISODATA algorithm, and H-K (Ho-Kashyap) algorithm. We present detailed implementations using both MATLAB and VC++ programming environments, including thorough explanations of algorithm theory, practical application scenarios, and step-by-step code examples. The MATLAB implementations leverage built-in statistical and matrix operations for efficient density estimation (Parzen), clustering optimization (ISODATA), and linear discriminant training (H-K), while the VC++ versions demonstrate low-level implementation details using object-oriented programming principles. Each algorithm section includes explanations of key functions, parameter optimization techniques, and performance considerations. Through this guide, readers will gain deep insights into both the theoretical foundations and practical implementation aspects of these essential pattern recognition methodologies.