Neural network for predicting values in non-linear functional mappings

The present invention relates to the field of artificial neural networks, in particular it relates to a single hidden layer artificial neural network for predicting values in non-linear functional mappings. A neural network for predicting values in non-linear functional mappings having a single hidden layer function generator () and an output layer (). The single hidden layer function generator () is operable to receive one or more mapping inputs (x1) and generate a plurality of terms () from each mapping input. The plurality of terms generated by the single hidden layer function generator () includes at least one trigonometric term selected from the group comprising sin(x1), sin(2x1), sin(3x1), cos(x1), cos(2xl), cos(3xl), cosec(xl), cotan(xl), and being free of Gaussian and Sigmoidal terms.