%0 Journal Article %1 FAN %A ?, %D 1998 %J CONGRESS ON COMPUTATIONAL INTELLIGENCE, FUZZ-IEEE'98 %K Fuzzy Hybrid Netowroks Networks Neural Systems %T FAN: LEARNING BY MEANS OF FREE ASSOCIATIVE NEURONS %U http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=624080&userType=inst %X In this paper we introduce a new learning method: Free Associative Neurons (FAN). FAN is composed by independent units with autonomous learning capability. The learning power of FAN is based on the association its units and on the use of granularity for representing information. As a method for representing complex environments, FAN can be used in Pattern Recognition, Classification and Diagnosis. This paper is focused on the principles governing FAN. We also discuss some results compared to well-known Artijicial Neural Network algorithms.

@article{FAN, abstract = {In this paper we introduce a new learning method: Free Associative Neurons (FAN). FAN is composed by independent units with autonomous learning capability. The learning power of FAN is based on the association its units and on the use of granularity for representing information. As a method for representing complex environments, FAN can be used in Pattern Recognition, Classification and Diagnosis. This paper is focused on the principles governing FAN. We also discuss some results compared to well-known Artijicial Neural Network algorithms.}, added-at = {2010-03-23T15:10:23.000+0100}, author = {?}, biburl = {https://www.bibsonomy.org/bibtex/228e25df0e4a91d6d7e5c7ba241b54727/dieval}, interhash = {0dcfc5a364bd29bb91398e5d738ca15b}, intrahash = {28e25df0e4a91d6d7e5c7ba241b54727}, journal = {CONGRESS ON COMPUTATIONAL INTELLIGENCE, FUZZ-IEEE'98}, keywords = {Fuzzy Hybrid Netowroks Networks Neural Systems}, timestamp = {2010-03-23T15:10:23.000+0100}, title = {FAN: LEARNING BY MEANS OF FREE ASSOCIATIVE NEURONS}, url = {http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=624080&userType=inst}, year = 1998 }