Fuzzy C-means Clustering using Pattern Recognition

The objective of this book is to talk about the usage of Fuzzy Logic in Pattern Recognition. There are different fuzzy approaches to recognize the pattern and the structure in data. The fuzzy approach that i have chosen to process the data completely depends on the type of data. Pattern recognition as we know involves various mathematical transforms so as to render the pattern or structure with the desired properties such as the identification of a probabilistic model which provides the explanation of the process generating the data clarity seen and so on. In this book I have focused to venture the ways in which Fuzzy Logic is applied to pattern recognition which is the collection of all approaches that understand, represent and process the data as segments and features by using fuzzy sets. The representation and processing depend on the selected fuzzy technique and on the problem to be solved. Most pattern recognition techniques involve treating the data as a variable applies standard processing techniques to it. Here I have discussed dynamic and efficient way of pattern recognition technique which should help to analyze evolving large number of data sets and making right decision

Autorentext

Karim Md. Ehsanul M.Sc in Mathematical Modeling and Simulation at Blekinge Institute of Technology,Sweden. M.Sc in Applied Mathematics at Khulna University, Bangladesh. B.Sc in Mathematics at Khulna University, Bangladesh.