DocumentCode
2767482
Title
Hamiltonian Neural Networks Based Classifiers and Mappings
Author
Sieñko, W. ; Zamojski, D.
Author_Institution
Member, IEEE, Department of Electrical Engineering, Gdynia Maritime University, Poland, e-mail: sienko@am.gdynia.pl
fYear
2006
fDate
16-21 July 2006
Firstpage
794
Lastpage
798
Abstract
We point out that Hamiltonian Neural Networks (HNN) and based on HNN orthogonal filters can be used as universal signal processors. To illustrate it, we propose a procedure for design of large scale mappings, classifiers and supervised learning systems.
Keywords
Adaptive systems; Artificial intelligence; Artificial neural networks; Equations; Filters; Large-scale systems; Neural networks; Neurons; Signal processing; Supervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2006. IJCNN '06. International Joint Conference on
Print_ISBN
0-7803-9490-9
Type
conf
DOI
10.1109/IJCNN.2006.246765
Filename
1716176
Link To Document