On a neural approximator to ODEs.
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.
Filici
Cristian
C
Comisión Nacional de Actividades Espaciales, 1063Buenos Aires, Argentina. cristian@conae.gov.ar
D000465:Algorithms; D000818:Animals; D006801:Humans; D008959:Models, Neurological; D016571:Neural Networks, Computer; D017711:Nonlinear Dynamics