Fuzzy C-means Model and Algorithm for Data Clustering

Abstract

Pattern recognition has become a very important field over the last decade since automation and computerization in many systems has led to large amount of data being stored in the databases.  The primary intention of pattern recognition is to automatically assist humans in analyzing the vast amount of available data and extracting useful knowledge from it. Many algorithms have been developed for many applications, especially for static pattern recognition.  Since the information of these processes can be non-deterministic over the time period, fuzzy approach can be applied to deal with this. In this work, fuzzy approach for optimization techniques in the pattern recognition will be implemented. It will show a fuzzy model for data clustering and feature extraction that best suits for the process of pattern recognition when we deal with non-crisp data.