In this paper, a supervised neural network training technique based on constrained optimization is developed for preserving prior knowledge of an input
Local minima and plateaus pose a serious problem in learning of neural networks. We investigate the hierarchical geometric structure of the parameter space of three-layer perceptr...
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
: This paper presents an algorithm, which is a hybrid-computing algorithm in representing solid model. The proposed algorithm contains two steps namely reconstruction and represent...