Granular computing focuses on formalizing information granules and unifying them to create a coherent methodological and developmental environment for intelligent system design and analysis. This innovative book presents the unified principles of granular computing along with its comprehensive algorithmic framework and design practices. It explores key concepts and formalisms as well as applications. It also emphasizes the need to consider information granularity as an important design asset that helps in the construction of more realistic models of real-world systems and in facilitating collaborative pursuits of system modeling.

Witold Pedrycz, Ph.D., is Professor and Canada Research Chair (CRC) in Computational Intelligence in the Department of Electrical and Computer Engineering, University of Alberta, Edmonton, Canada. He is also with the Systems Research Institute of the Polish Academy of Sciences, Warsaw, Poland and King Abdulaziz University, Saudi Arabia. In 2009, Dr. Pedrycz was elected a foreign member of the Polish Academy of Sciences. He is a Fellow of the Royal Society of Canada, the Institute of Electronic and Electrical Engineers (IEEE), International Fuzzy Systems Association (IFSA), International Society of Management Engineers, Engineers Canada, and The Engineering Institute of Canada. He is editor-in-chief of Information Sciences and editor-in-chief of IEEE Transactions on Systems, Man, and Cybernetics, Part A. He currently serves as an associate editor of IEEE Transactions on Fuzzy Systems and a number of other international journals. In 2007, he received the prestigious Norbert Wiener award from the IEEE Systems, Man, and Cybernetics Society. Dr. Pedrycz is a recipient of the IEEE Canada Computer Engineering Medal. In 2009, he received a Cajastur Prize for Soft Computing from the European Centre for Soft Computing for "pioneering and multifaceted contributions to granular computing." In 2013 he received a prestigious Killam Prize.

Information Granularity, Information Granules, and Granular Computing. Key Formalisms for Representation of Information Granules and Processing Mechanisms. Information Granules of Higher Type and Higher Order, and Hybrid Information Granules. Representation of Information Granules. The Design of Information Granules. Optimal Allocation of Information Granularity: Building Granular Mappings. Granular Description of Data and Pattern Classification. Granular Models: Architectures and Development. Granular Time Series. From Models to Granular Models. Collaborative and Linguistic Models of Decision Making. Index.