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Zhang, N., Wu, W. and Zheng, G. (2006) Convergence of Gradient Method with Momentum for Two-Layer Feedforward Neural Networks. IEEE Transactions Neural Networks, 17, 522-525.
https://doi.org/10.1109/TNN.2005.863460

has been cited by the following article:

• TITLE: A Study on the Convergence of Gradient Method with Momentum for Sigma-Pi-Sigma Neural Networks

  AUTHORS: Xun Zhang, Naimin Zhang

  KEYWORDS: Sigma-Pi-Sigma Neural Network, Momentum Term, Gradient Method, Convergence

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.6 No.4, April 26, 2018

  ABSTRACT: In this paper, a gradient method with momentum for sigma-pi-sigma neural networks (SPSNN) is considered in order to accelerate the convergence of the learning procedure for the network weights. The momentum coefficient is chosen in an adaptive manner, and the corresponding weak convergence and strong convergence results are proved.