Training of recurrent Internal Symmetry Networks by backpropagation

Internal symmetry networks are a recently developed class of cellular neural network inspired by the phenomenon of internal symmetry in quantum physics. Their hidden unit activations are acted on non-trivially by the dihedral group of symmetries of the square. Here, we extend Internal symmetry networks to include recurrent connections, and train them by backpropagation to perform two simple image processing tasks.