Institute of Information Theories and Applications FOI ITHEA
Abstract:
In the paper new non-conventional growing neural network is proposed. It coincides with the Cascade-
Correlation Learning Architecture structurally, but uses ortho-neurons as basic structure units, which can be
adjusted using linear tuning procedures. As compared with conventional approximating neural networks proposed
approach allows significantly to reduce time required for weight coefficients adjustment and the training dataset
size.