Enhancing neural network functionality with ensemble encoding

The authors discuss ensemble coding, a biologically motivated data representation scheme, which uses multiple receptors with overlapping receptive fields to encode analog inputs to multilayer perceptron (MLP) networks. By generating a distributed representation for input data, ensemble encoding enhances the node connection function for hidden-layer neurons. The added flexibility in constructing nonlinear internal mappings afforded by ensemble encoding is demonstrated through a function approximation example