A new paper on clustering disparate data

[Vassilis Petridis]

Dear Connectionists,

We would like to  inform you that the paper

V. Petridis, and V.G. Kaburlasos, "Fuzzy Lattice Neural Network (FLNN):
A Hybrid Model for Learning", IEEE Transactions on Neural Networks,
vol. 9, no. 5, September 1998, pp. 877-890,

can be accessed at

         http://skiron.control.ee.auth.gr/post1990.html


It has already been stated in the abstract of our above paper that
the FLNN draws on Carpenter-Grossberg's Adaptive Resonance Theory (ART)
as well as it draws on Simpson's Min-Max neurocomputing principles.
Nevertheless we are going to point out herein that the FLNN is not
merely a modified version of the previous well known neural paradigms.

The important difference is that the FLNN is applicable to data types
with the structure of a mathematical lattice. As a consequence, the
FLNN is applicable apart from the conventional Euclidean space to
other domains as well. For instance in the above paper we demonstrate
a learning example in the domain of fuzzy sets over a universe of
discourse. We treat other domains in forthcoming publications.

Learning and decision-making by the FLNN can both make common sense
and be subject to rigorous mathematical analysis. FLNN is a specific
scheme within the framework of fuzzy lattices (or, FL-framework) which
is presented briefly in the above paper.

Apart from (possible) interest in FLNN's "off the mainstream"
mathematics, there exists a significant practical potential underlying
the employment of the FLNN. That is the capacity to treat jointly and
rigorously disparate data. For example the FLNN can treat
simultaneously - and with rigour - such disparate data as real
numbers, fuzzy sets, propositional statements, symbols, etc. An
example of processing disparate data is information filtering and
retrieval from the web. We point out that to the best of our knowledge
this is a unique capacity of the FLNN alone.  In this sense the FLNN
can emulate human's capacity for processing jointly disparate data.


Comments are welcome.

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Professor Vassilios Petridis
Dept. of Electrical and Computer Eng.
Faculty of Engineering
Aristotle University of Thessaloniki
GR54006 Thessaloniki, GREECE
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email: petridis at vergina.eng.auth.gr
phone: +3031 996331
fax  : +3031 996367
web  : http://control.ee.auth.gr/