A feedforward neural network based on multi-valued neurons is considered in the paper. It is shown that using a traditional feedforward architecture and a high functionality multi-...
Learning to solve small instances of a problem should help in solving large instances. Unfortunately, most neural network architectures do not exhibit this form of scalability. Our...
In this paper, we describe a means for automatically building very large neural networks (VLNNs) from definition texts in machine-readable dictionaries, and demonstrate the use of...
Abstract. In our previous studies, Genetic Programming (GP), Probabilistic Incremental Program Evolution (PIPE) and Ant Programming (AP) have been used to optimal design of Flexibl...
Abstract A lateral-inhibition type neural field model with restricted connections is presented here and represents an experimental extension of the Continuum Neural Field Theory (C...