Problem and Strategy: Overfitting in Recurrent Cycles of Internal Symmetry Networks by Back Propagation

Abstract

Overfitting is an important topic in Neural Network. Internal Symmetry Networks are a new modern Cellular Neural Networks inspired by the phenomenon of internal symmetry in quantum physics. Recurrent Internal Symmetry Networks are just studied very recently. In this paper, overfitting in recurrent cycles of Internal Symmetry Networks is analyzed. Back propagation is trained for an image processing task.