Volume 26, Issue 4
Convergence of Gradient Method with Momentum for Back-Propagation Neural Networks

Wei Wu, Naimin Zhang, Zhengxue Li, Long Li & Yan Liu

DOI:

J. Comp. Math., 26 (2008), pp. 613-623

Published online: 2008-08

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  • Abstract

In this work, a gradient method with momentum for BP neural networks is considered. The momentum coefficient is chosen in an adaptive manner to accelerate and stabilize the learning procedure of the network weights. Corresponding convergence results are proved.

  • Keywords

Back-propagation (BP) neural networks Gradient method Momentum Convergence

  • AMS Subject Headings

68Q32 68T05.

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JCM-26-613, author = {}, title = {Convergence of Gradient Method with Momentum for Back-Propagation Neural Networks}, journal = {Journal of Computational Mathematics}, year = {2008}, volume = {26}, number = {4}, pages = {613--623}, abstract = { In this work, a gradient method with momentum for BP neural networks is considered. The momentum coefficient is chosen in an adaptive manner to accelerate and stabilize the learning procedure of the network weights. Corresponding convergence results are proved.}, issn = {1991-7139}, doi = {https://doi.org/}, url = {http://global-sci.org/intro/article_detail/jcm/8645.html} }
TY - JOUR T1 - Convergence of Gradient Method with Momentum for Back-Propagation Neural Networks JO - Journal of Computational Mathematics VL - 4 SP - 613 EP - 623 PY - 2008 DA - 2008/08 SN - 26 DO - http://doi.org/ UR - https://global-sci.org/intro/article_detail/jcm/8645.html KW - Back-propagation (BP) neural networks KW - Gradient method KW - Momentum KW - Convergence AB - In this work, a gradient method with momentum for BP neural networks is considered. The momentum coefficient is chosen in an adaptive manner to accelerate and stabilize the learning procedure of the network weights. Corresponding convergence results are proved.
Wei Wu, Naimin Zhang, Zhengxue Li, Long Li & Yan Liu. (1970). Convergence of Gradient Method with Momentum for Back-Propagation Neural Networks. Journal of Computational Mathematics. 26 (4). 613-623. doi:
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