International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 71 - Issue 13 |
Published: June 2013 |
Authors: Amarpal Singh, Piyush Saxena, Sangeeta Lalwani |
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Amarpal Singh, Piyush Saxena, Sangeeta Lalwani . A Study of Various Training Algorithms on Neural Network for Angle based Triangular Problem. International Journal of Computer Applications. 71, 13 (June 2013), 30-36. DOI=10.5120/12420-8988
@article{ 10.5120/12420-8988, author = { Amarpal Singh,Piyush Saxena,Sangeeta Lalwani }, title = { A Study of Various Training Algorithms on Neural Network for Angle based Triangular Problem }, journal = { International Journal of Computer Applications }, year = { 2013 }, volume = { 71 }, number = { 13 }, pages = { 30-36 }, doi = { 10.5120/12420-8988 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2013 %A Amarpal Singh %A Piyush Saxena %A Sangeeta Lalwani %T A Study of Various Training Algorithms on Neural Network for Angle based Triangular Problem%T %J International Journal of Computer Applications %V 71 %N 13 %P 30-36 %R 10.5120/12420-8988 %I Foundation of Computer Science (FCS), NY, USA
This paper examines the study of various feed forward back-propagation neural network training algorithms and performance of different radial basis function neural network for angle based triangular problem. The training algorithms in feed forward back-propagation neural network comprise of Scale Gradient Conjugate Back-Propagation (BP), Conjugate Gradient BP through Polak-Riebre updates, Conjugate Gradient BP through Fletcher-Reeves updates, One Secant BP and Resilent BP. The final result of each training algorithm for angle based triangular problem will also be discussed and compared.