Fuzzy Learning and Applications

With low computational complexity and relatively short development time, Fuzzy Logic is an indispensable tool for engineering applications. The field is growing at an unprecedented rate, and there is a need for a book that describes essential tools, applications, examples, and perspectives in the field of fuzzy learning. The editors of Fuzzy Learni

Russo, Marco; Jain, Lakhmi C.

Evolutionary Fuzzy Learning, M. Russo A Stored-Programmable Mixed-Signal Fuzzy Controller Chip with Supervised Learning Capabilities, F. Vidal-Verdú, R. Navas, M. Delgado-Restituto, and A. Rodríguez-Vázquez Fuzzy Modeling in a Multi-Agent Framework for Learning in Autonomous Systems, Juan A. Botía, Humberto Martínez Barberá, and Antonio F. Gómez Skármeta Learning Techniques for Supervised Fuzzy Classifiers, F. Masulli and A. Sperduti Multistage Fuzzy Control, Z.M. Yeh and H.P. Chen Learning Fuzzy Systems, A. Lofti Application of Fuzzy Modeling to Analysis of Rowing Boat Speed, K. Tachibana, T. Furuhashi, M. Shimoda, Y. Kawakami, and T. Fukunaga A Novel Fuzzy Approach to Hopfield Coefficients Determination, S. Cavalieri and M. Russo Fuzzy Control of a CD Player Focusing System, L. Fortuna, G. Muscato, R. Caponetto, and M.G. Xibilia A Neuro-Fuzzy Scheduler for a Multi-Media Web Server, Z. Ali, A. Ghafoor, and C.S.G. Lee A Neuro-Fuzzy System Based on Logical Interpretation of If-Then Rules, J. Leski and N. Henzel