Fuzzy higher type information granules from an uncertainty measurement

Hierarchical Architectures of Fuzzy Models: From Type-1 fuzzy sets to Information Granules of Higher Type

Complex phenomena are perceived from different perspectives, diversified conceptual points of view and at various levels of granularity. Symbolic and sub-symbolic processing becomes an inherently visible computing practice. Distributed nature of perception becomes reflected in topologies of multi-agent systems. All of these facets challenge the well-established paradigms of system modeling incl...

Fuzzy information granules in time series data

Michael R. Berthold,* Marco Ortolani, David Patterson, Frank Höppner, Ondine Callan, Heiko Hofer University of Konstanz, 78457 Konstanz, Germany University of Palermo, Department of Electrical Engineering, Viale delle Scienze 90128 Palermo, Italy Tripos, Inc., 1699 S. Hanley Road, St. Louis, MO 64133 University of Applied Sciences, Emden, Department of Electrical Engineering and Computer Scienc...

Fuzzy sets, uncertainty and information

From Data to Information Granules

Fuzzy Information Granules: a Compact, Transparent and Efficient Representation

1 This paper presents a method to construct information granules that provide a relevant description of experimental observations and, at the same time, are represented in a compact and semantically sound form. The method works by first granulating data through a fuzzy clustering algorithm, and then representing granules in form of fuzzy sets. Specifically, an optimal Gaussian functional form f...