A Generalized Net Model of the Deep Learning Algorithm
Konferenz: ANNA '18 - Advances in Neural Networks and Applications 2018
15.09.2018 - 17.09.2018 in St. St. Konstantin and Elena Resort, Bulgaria
Tagungsband: ANNA '18
Seiten: 5Sprache: EnglischTyp: PDFPersönliche VDE-Mitglieder erhalten auf diesen Artikel 10% Rabatt
Yovcheva, Plamena; Petkov, Todor; Sotirov, Sotir (University of Prof. D-R Asen Zlatarov – Bourgas, Intelligent Systems Laboratory, Bulgaria)
In this paper a generalized net model of the Deep Learning Neural Network Algorithm (DLNNA) is presented. A DLNN is a self-organizing network with the ability to recognize patterns based on the difference of their form. A DLNN is able to correctly identify an image, speech recognition and natural language processing. Self-organization in the DLNN is also realized uncontrollably. Training for self-organizing DLNN takes only a collection of recurring patterns in the recognizable image and does not need the information for categories that include templates. The output producing process is presented by a Generalized net model.