Generalized Dai-Yuan conjugate gradient algorithm for training multi-layer feed-forward neural networks
DOI:
https://doi.org/10.25130/tjps.v24i1.341Abstract
In this paper, we will present different type of CG algorithms depending on Peary conjugacy condition. The new conjugate gradient training (GDY) algorithm using to train MFNNs and prove it's descent property and global convergence for it and then we tested the behavior of this algorithm in the training of artificial neural networks and compared it with known algorithms in this field through two types of issues.
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