(untitled) (JOURNAL OF UNIVERSITY OF BABYLON for Pure and Applied Sciences, 2019)
Many papers introduced about the approximation of continuous functions using neural networks. In this paper we use neural network to approximate functions in spaces for p . We study the approximation for functions defined on the complete real line using neural networks with radial basis having constant weight. We also use convolution to approximate functions in spaces for a compact interval using radial basis function neural networks of constant weights.