Abstract
The paper proposes a new classification scheme for relational patterns. The classifier design is linked with a decomposition problem of fuzzy relations. Two different optimization environments are exploited: the first one is based upon standard gradient-based methods while the second introduces an induced fuzzy neural network and exploits its learning capabilities. Simulation studies include synthetic and experimental collections of patterns.