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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Natural Gradient Descent for Training Stochastic Complex-Valued Neural Networks
Digital Object Identifier (DOI) : 10.14569/IJACSA.2014.050729
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 7, 2014.
Abstract: In this paper, the natural gradient descent method for the multilayer stochastic complex-valued neural networks is considered, and the natural gradient is given for a single stochastic complex-valued neuron as an example. Since the space of the learnable parameters of stochastic complex-valued neural networks is not the Euclidean space but a curved manifold, the complex-valued natural gradient method is expected to exhibit excellent learning performance.
Keywords: Neural network; Complex number; Learning; Singular point
Tohru Nitta, “Natural Gradient Descent for Training Stochastic Complex-Valued Neural Networks” International Journal of Advanced Computer Science and Applications(IJACSA), 5(7), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050729
@article{Nitta2014,
title = {Natural Gradient Descent for Training Stochastic Complex-Valued Neural Networks},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050729},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050729},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {7},
author = {Tohru Nitta}
}
