In this paper, we study a natural extension of Multi-Layer Perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional...
In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Background: Several supervised and unsupervised learning tools are available to classify functional genomics data. However, relatively less attention has been given to exploratory...
Many processes are composed of a n-fold repetition of some simpler process. If the whole process can be modeled with a neural network, we present a method to derive a model of the...
Many real processes are composed of a n-fold repetition of some simpler process. If the whole process can be modelled with a neural network, we present a method to derive a model ...