International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 71 - Number 13 |
Year of Publication: 2013 |
Authors: Amarpal Singh, Piyush Saxena, Sangeeta Lalwani |
10.5120/12420-8988 |
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
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.