A theory and methodology are presented for training artificial neural networks in a general setting. Starting with defining general concepts, and analyzing associated properties of artificial neural networks, the authors formalize, categorize, and characterize artificial neural networks from a system point of view. They focus on the analysis aspect of artificial neural nets to address and investigate trainability and representability; on the synthesis aspect of artificial neural nets to provide design principles to the systems; and on the algorithmic aspect of the artificial neural nets to develop an effective and efficient learning paradigm.
|Number of pages||7|
|Publication status||Published - 1989|
|Event||IJCNN International Joint Conference on Neural Networks - Washington, DC, USA|
Duration: 18 Jun 1989 → 22 Jun 1989
|Conference||IJCNN International Joint Conference on Neural Networks|
|City||Washington, DC, USA|
|Period||18/06/89 → 22/06/89|