Granular Computing

Granular Computing is concerned with constructing and processing carried out at the level of information granules. Using information granules, we comprehend the world and interact with it, no matter which intelligent endeavor this may involve. The landscape of granular computing is immensely rich and involves set theory (interval mathematics), fuzzy sets, rough sets, random sets linked together in a highly synergetic environment. This volume is a first comprehensive treatment of this emerging paradigm and embraces its fundamentals, underlying methodological framework, and a sound algorithmic environment. The panoply of applications covered includes system identification, telecommunications, linguistics and music processing. Written by experts in the field, this volume will appeal to all developing intelligent systems, either working at the methodological level or interested in detailed system realization.

A well-balanced approach to the area covering the methodology, detailed algorithms and computational aspects of Granular Computing, with abundant illustrative material The reader becomes familiar with the paradigm of Granular Computing and its usage to the design of intelligent systems Includes supplementary material: sn.pub/extras

Inhalt
Interval Arithmetic and Interval Analysis: An Introduction.- Interval and Ellipsoidal Uncertainty Models.- Nonlinear Bounded-Error Parameter Estimation Using Interval Computation.- Random Sets: Theory and Applications.- Rough Sets and Boolean Reasoning..- Granulation and Nearest Neighborhoods: Rough Set Approach..- An Inquiry into the Theory of Defuzzification.- Fuzzy Partitioning Methods.- A Coding Method to Handle Linguistic Variables.- A Formal Theory of Fuzzy Natural Language Quantification and its Role in Granular Computing..- Granularity and Specificity in Fuzzy Rule-Based Systems.- Granular Computing in Neural Networks.- Fuzzy Clustering for Multiple-Model Approaches in System Identification and Control..- Information Granulation in Automated Modeling.- Optical Music Recognition: the Case of Granular Computing.- Modeling MPEG VBR Video Traffic Using Type-2 Fuzzy Logic Systems.- Induction of Rules about Complications with the Use of Rough Sets.