Linguistic Fuzzy Cognitive Map (LFCM) for pattern recognition

This paper introduces a preliminary extension of the Fuzzy Cognitive Map (FCM) architecture based on Lattice Computing (LC) techniques namely Linguistic Fuzzy Cognitive Maps (LFCM). The proposed LFCM is able to handle large scale data in pattern classification applications. This enhancement is achieved by applying a novel data meta-representation, defined in a mathematical lattice, including several advantages. Based on this mechanism a new FCM classifier model is constructed and its performance is studied herein. Preliminary experimental results are both promising and competitive. Future work extensions are discussed.