An enhancement to MLP model to enforce closed decision regions

Abstract

Describes a modification of the basic MLP (multilayer perceptron) model implemented to improve its capability to enforce closed decision regions. The authors' proposal is to use hyperspheres instead of hyperplanes on the first hidden layer, and in turn combine them through the next layers. After training, the decision regions will be naturally closed because they are built on simple computational elements which will fire only if the pattern will fall in the hypersphere receptive fields. The training is achieved by applying a modification of the basic backpropagation error without use of ad-hoc algorithms. A two-dimensional example is reported.<>