1 research outputs found
On Interference of Signals and Generalization in Feedforward Neural Networks
This paper studies how the generalization ability of neurons can be affected
by mutual processing of different signals. This study is done on the basis of a
feedforward artificial neural network. The mutual processing of signals can
possibly be a good model of patterns in a set generalized by a neural network
and in effect may improve generalization. In this paper it is discussed that
the interference may also cause a highly random generalization. Adaptive
activation functions are discussed as a way of reducing that type of
generalization. A test of a feedforward neural network is performed that shows
the discussed random generalization.Comment: 6 pages, 3 figures. Some changes in text to make it more concis