This Text starts with a detailed overview of the Applications of neural Networks, illustrating its importance. The current problems present in the existing training algorithms like Back-Propagation, Newtons algorithm and the popular Levenberg-Marquardt algorithm are reviewed. The use of Multiple Optimal learning factors are explored in the text, followed by its complete analysis and possible methods of improvisation. All the training algorithms are implemented in Visual Studio 2005, and tested with universally accepted data files. It is observed that the Improvement of Multiple Optimal Learning Factors suggested in this text, provides almost the same effectiveness of the Levenberg-Marquardt algorithm with much lesser computational cost.
Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.
Praveen Jesudhas is a Research Engineer at ProdEX Technologies. He holds a Master's Degree in Electrical engineering from UT Arlington, USA. He has previously held positions as software Application Developer and Pattern Recognition Intern.His research interests include image processing,pattern recognition and machine learning
„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Analysis and Improvement of Feed-forward network training | With Complete Implementation | P. Praveen Jesudhas (u. a.) | Taschenbuch | 56 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783845441016 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Artikel-Nr. 106818403
Anzahl: 5 verfügbar