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FUZZ-IEEE 2009 - Special Session

Theory and Applications of Fuzzy Signatures

Organizers: Sumudu Mendis

Tom Gedeon

Collage of Engineering and Computer Science,

Australian National University,

Australia

This special session will focus on theory and applications of Fuzzy Signature but we welcome papers from other areas in general fuzzy hierarchical organization of data and aggregation functions.

List of Key Words:

1. Fuzzy hierarchical organization of data and aggregation functions.

2. Theory of Fuzzy Signatures, and Polymorphic Fuzzy Signatures.

3. Aggregation Operators for Polymorphic Fuzzy Signatures.

4. Identification of input subspaces, aggregation operators, and structure of Polymorphic Fuzzy Signatures.

5. Applications of Fuzzy Signatures and Polymorphic Fuzzy Signatures.

Fuzzy Signatures:

In Computational Intelligence, in most situations we face problems with the input data being complex and complicated. Some parts of the data are missing or not known yet. In such scenarios, human beings still could come to a decision based on the available data but it is an increasingly difficult problem to construct an effective complex decision model. The concept of fuzzy signatures was introduced to help model these kinds of problems.

Fuzzy signatures are sparse hierarchical multi-aggregative fuzzy descriptors, which are aggregated to an atomic value or compared with another fuzzy signature to get a final degree of match. Fuzzy signatures use the hierarchical structure present within a data set to decompose its underlying global relation into several hierarchically organized local relations that can be modeled easily with sets of input sub-spaces. This means that one or several components of the structure are determined at a higher level by a sub-tree of other components with a meaningful aggregation that is specific to that sub-tree. When problems occur with some missing components, the resulting structures of the problem may slightly differ. That means we are still able to find an approximated decomposition to its global relation with the available branches. That is, these available data can be compared and aggregated to a final degree of match.

Contact:

1. SumuduMendis (sumudu@cs.anu.edu.au)

ANU College of Engineering and Computer Science

Building 108, CS&IT

The Australian National University

Canberra ACT 0200 Australia

T: +61 2 6125 2646

F: +61 2 6125 0010