Face recognition by concept formation neural structure

In this paper, we develop a new neural model that deals with continuation value of inputs for some practical applications of pattern recognition task. An essential core of the model is use of a novel vector representation of a target concept in a multi-level informational hierarchy that makes the model possess category formation ability from incomplete observation of the target. Simulation results demonstrate the usefulness of the model for a facial image recognition task, even if it is carried out under an incremental and unsupervised learning environment.