A novel conjugate gradient method with generalized Armijo search for efficient training of feedforward neural networks
Abstract
In this paper, a novel multilayer backpropagation (BP) neural network model is proposed based on conjugate gradient (CG) method with generalized Armijo search. The presented algorithm requires low memory and performs fast convergent speed in practical applications. One reason is that the constructed conjugate direction guarantees the sufficient descent behavior in minimizing the given objective function. The other stems from the fact that the...
Paper Details
Title
A novel conjugate gradient method with generalized Armijo search for efficient training of feedforward neural networks
Published Date
Jan 1, 2018
Journal
Volume
275
Pages
308 - 316
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