Convergence of BP Algorithm for Training MLP with Linear Output
Numer. Math. J. Chinese Univ. (English Ser.)(English Ser.) 16 (2007), pp. 193-202
Published online: 2007-08
Cited by
Export citation
- BibTex
- RIS
- TXT
@Article{NM-16-193,
author = { H. M. Shao, W. Wu and W. B. Liu},
title = {Convergence of BP Algorithm for Training MLP with Linear Output},
journal = {Numerical Mathematics, a Journal of Chinese Universities},
year = {2007},
volume = {16},
number = {3},
pages = {193--202},
abstract = {
The capability of multilayer perceptrons (MLPs) for approximating
continuous functions with arbitrary accuracy has been demonstrated
in the past decades. Back propagation $($BP$)$ algorithm is the most
popular learning algorithm for training of MLPs. In this paper, a
simple iteration formula is used to select the learning rate for
each cycle of training procedure, and a convergence result is
presented for the BP algorithm for training MLP with a hidden layer
and a linear output unit. The monotonicity of the error function is
also guaranteed during the training iteration.},
issn = {},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/nm/8053.html}
}
TY - JOUR
T1 - Convergence of BP Algorithm for Training MLP with Linear Output
AU - H. M. Shao, W. Wu & W. B. Liu
JO - Numerical Mathematics, a Journal of Chinese Universities
VL - 3
SP - 193
EP - 202
PY - 2007
DA - 2007/08
SN - 16
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/nm/8053.html
KW -
AB -
The capability of multilayer perceptrons (MLPs) for approximating
continuous functions with arbitrary accuracy has been demonstrated
in the past decades. Back propagation $($BP$)$ algorithm is the most
popular learning algorithm for training of MLPs. In this paper, a
simple iteration formula is used to select the learning rate for
each cycle of training procedure, and a convergence result is
presented for the BP algorithm for training MLP with a hidden layer
and a linear output unit. The monotonicity of the error function is
also guaranteed during the training iteration.
H. M. Shao, W. Wu & W. B. Liu. (1970). Convergence of BP Algorithm for Training MLP with Linear Output.
Numerical Mathematics, a Journal of Chinese Universities. 16 (3).
193-202.
doi:
Copy to clipboard