On a Neural Approximator to ODEs
Cristian Filici · IEEE Transactions on Neural Networks · 2008
The object of this brief is to present and analyze the training of a single-layer neural network in order to solve ordinary differential equations (ODEs). Properties of the approximator are derived and some examples of its application are shown.