WITOLD PEDRYCZ, PHD, is a Professor and Canada Research Chair at the University of Alberta, Canada. He is also with the Systems Research Institute of The Polish Academy of Sciences, Warsaw, Poland. Dr. Pedrycz is a Fellow of the IEEE, has authored nine research monographs, edited six volumes, and has written numerous papers in computational intelligence, granular computing, pattern recognition, quantitative software engineering, and data mining.

* A comprehensive coverage of emerging and current technology dealing with heterogeneous sources of information, including data, design hints, reinforcement signals from external datasets, and related topics
* Covers all necessary prerequisites, and if necessary,additional explanations of more advanced topics, to make abstract concepts more tangible
* Includes illustrative material andwell-known experimentsto offer hands-on experience

Foreword.
Preface.
1. Clustering and Fuzzy Clustering.
2. Computing with Granular Information: Fuzzy Sets and Fuzzy Relations.
3. Logic-Oriented Neurocomputing.
4. Conditional Fuzzy Clustering.
5. Clustering with Partial Supervision.
6. Principles of Knowledge-Based Guidance in Fuzzy Clustering.
7. Collaborative Clustering.
8. Directional Clustering.
9. Fuzzy Relational Clustering.
10. Fuzzy Clustering of Heterogeneous Patterns.
11. Hyperbox Models of Granular Data: The Tchebyschev FCM.
12. Genetic Tolerance Fuzzy Neural Networks.
13. Granular Prototyping.
14. Granular Mappings.
15. Linguistic Modeling.
Bibliography.
Index.