A Generalized Net Model of the Deep Learning Neural Network

Conference: ANNA '18 - Advances in Neural Networks and Applications 2018
09/15/2018 - 09/17/2018 at St. St. Konstantin and Elena Resort, Bulgaria

Proceedings: ANNA '18

Pages: 4Language: englishTyp: PDF

Personal VDE Members are entitled to a 10% discount on this title

Sotirov, Sotir; Sotirova, Evdokia; Bureva, Veselina; Petkov, Todor; Popov, Stanislav; Bozov, Hristo; Tsolova, Diana; Georgieva, Vania (University of Prof. D-R Asen Zlatarov – Bourgas, Intelligent Systems Laboratory, Bulgaria)
Shannon, Anthony (Warrane College, The University of New South Wales, Kensington, Australia)

In this paper a generalized net model of a deep learning neural network is presented. A deep learning neural network generally refers to methods that map data via multiple levels of abstraction. The implementation of deep learning comes in the form of feedforward neural networks, where levels of abstraction are modelled by different types of tools. The output producing process is presented by a Generalized Net model.