DocumentCode
2347952
Title
Multilayer neural networks training methodic
Author
Golovko, Vladimir ; Maniakov, Nikolaj ; Makhnist, Leonid
Author_Institution
Lab. of Artificial Intelligence, Brest State Tech. Univ.
fYear
2003
fDate
8-10 Sept. 2003
Firstpage
185
Lastpage
190
Abstract
We propose three new techniques for training of multilayer neural networks. Its basic concept is based on the gradient descent method. For every methodic are showed formulas for calculation of the adaptive training steps. Matrix algorithmization for all of this techniques are very helpful in its program realization
Keywords
feedforward neural nets; gradient methods; learning (artificial intelligence); adaptive training step; gradient descent method; matrix algorithmization; multilayer neural network training; program realization; Artificial intelligence; Artificial neural networks; Chaos; Feedforward neural networks; Laboratories; Least squares approximation; Mathematics; Multi-layer neural network; Neural networks; Neurons;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2003. Proceedings of the Second IEEE International Workshop on
Conference_Location
Lviv
Print_ISBN
0-7803-8138-6
Type
conf
DOI
10.1109/IDAACS.2003.1249545
Filename
1249545
Link To Document