Leszek Rutkowski
Technical University of Czestochowa, Czestochowa, Poland

Abstract
In the tutorial we incorporate various flexibility parameters to the construction of neuro-fuzzy systems. This approach dramatically improves their performance, allowing the systems to perfectly represent the pattern encoded in data. It should be noted that the tutorial provides a framework for the unification, construction and development of neuro fuzzy systems. It presents complete algorithms in a systematic and structured fashion, easing the understanding and implementation. The strength of the tutorial is that it provides tools for possible applications in business and economics, medicine and bioengineering, automatic control, robotics, decision theory and expert systems.
In the tutorial we discuss a new class of neuro fuzzy systems characterized by automatic determination of a fuzzy inference (Mamdani/ logical) in the process of learning. Consequently, the structure of the system is determined in the process of learning. In addition to automatic determination of a system type, we introduce several flexibility concepts in the design of neuro fuzzy systems: softness to fuzzy implication operators, to the aggregation of rules and to the connectives of antecedents; certainty weights to the aggregation of rules and to the connectives of antecedents; parameterized families of t norms and t conorms to fuzzy implication operators, to the aggregation of rules and to the connectives of antecedents.

Speaker
Leszek Rutkowski was born in Wroclaw, Poland, in 1952. He received M. Sc., Ph. D. and D. Sc. degrees in 1977, 1980, 1986, respectively, all from the Technical University of Wroclaw, Poland. Since 1980, he has been with the Technical University of Czestochowa where he is currently a Professor and Chairman of the Computer Engineering Department. From 1987 to 1990 he held a visiting position in the School of Electrical and Computer Engineering at Oklahoma State University. His research interests include neural networks, fuzzy systems, computational intelligence, pattern recognition and systems identification. He published over 120 technical papers including 17 in various series IEEE Transactions. He is the author of the books "New Soft Computing Techniques for System Modelling, Pattern Classification and Image Processing" published by Springer (2004), "Flexible Neuro-Fuzzy Systems" published by Kluwer Academic Publishers (2004), "Adaptive Filters and Adaptive Signal Processing" (in Polish), and co-author of two others (in Polish) "Neural Networks, Genetic Algorithms and Fuzzy Systems" and "Neural Networks for Image Compression". He is also President and Founder of the Polish Neural Networks Society and Chairman of the Polish Chapter of the IEEE Computational Intelligence Society. He organized and served as General Chair of the international conferences on neural networks, soft computing and artificial intelligence held in Poland in: 1996, 1997, 1999, 2000, 2002. Prof. Leszek Rutkowski is an Associate Editor of the IEEE Transactions on Neural Networks and recently elected Member of the Polish Academy of Sciences. He is also the recipient of the 2005 IEEE Transactions Neural Networks Outstanding Paper Award. In November 2004 he was awarded by the IEEE Fellow Membership Grade for contributions to neurocomputing and flexible fuzzy systems.