Multimodal Pattern Classifiers with Feedback of Class Memberships

摘要

Feedback of class memberships is incorporated into multimodal pattern classifiers and their unsupervised learn- ing algorithm is presented. Classification decision at low levels is revised by the feedback information which also enables the re- construction of patterns at low levels. The effects of the feedback are examined for the McGurk effect by using a simple model.