Multimodal pattern classifiers with feedback of class memberships
Feedback of class memberships is incorporated into multimodal pattern classifiers and their unsupervised learning algorithm is presented. Classification decision at low levels is revised by the feedback information which also enables the reconstruction of patterns at low levers. The effects of the feedback are examined for the McGurk effect by using a simple model.
multimodal pattern classifier feedback mcgurk effect