Real-Time Construction of Neural Networks

A stepwise two-stage algorithm is proposed for real-time construction of generalized single-layer networks (GSLNs). The first stage of this algorithm generates a network using a forward selection procedure, which is then reviewed at the second stage to replace insignificant neural nodes. The main contribution of this paper is that these two stages are performed within one regression context using Cholesky decomposition, leading to significantly neural network performance and concise real-time network construction procedures.