A theory for learning by weight flow on Stiefel-Grassman manifold

Recently we introduced the concept of neural network learning on Stiefel-Gr assman manifold for multilayer perceptron-like networks. Contributions of o ther authors have also appeared in the scientific literature about this top ic. This article presents a general theory for it and illustrates how exist ing theories may be explained within the general framework proposed here.