Empirical evaluation of the improved Rprop learning algorithm
Research output: Contribution to journal › Journal article › Research › peer-review
Standard
Empirical evaluation of the improved Rprop learning algorithm. / Igel, Christian; Hüsken, M.
In: Neurocomputing, Vol. 50, 2003, p. 105-123.Research output: Contribution to journal › Journal article › Research › peer-review
Harvard
Igel, C & Hüsken, M 2003, 'Empirical evaluation of the improved Rprop learning algorithm', Neurocomputing, vol. 50, pp. 105-123. https://doi.org/10.1016/S0925-2312(01)00700-7
APA
Igel, C., & Hüsken, M. (2003). Empirical evaluation of the improved Rprop learning algorithm. Neurocomputing, 50, 105-123. https://doi.org/10.1016/S0925-2312(01)00700-7
Vancouver
Igel C, Hüsken M. Empirical evaluation of the improved Rprop learning algorithm. Neurocomputing. 2003;50:105-123. https://doi.org/10.1016/S0925-2312(01)00700-7
Author
Bibtex
@article{84044b1bc2b14184a19704ef76763c9e,
title = "Empirical evaluation of the improved Rprop learning algorithm",
author = "Christian Igel and M. H{\"u}sken",
year = "2003",
doi = "10.1016/S0925-2312(01)00700-7",
language = "English",
volume = "50",
pages = "105--123",
journal = "Neurocomputing",
issn = "0925-2312",
publisher = "Elsevier",
}
RIS
TY - JOUR
T1 - Empirical evaluation of the improved Rprop learning algorithm
AU - Igel, Christian
AU - Hüsken, M.
PY - 2003
Y1 - 2003
U2 - 10.1016/S0925-2312(01)00700-7
DO - 10.1016/S0925-2312(01)00700-7
M3 - Journal article
VL - 50
SP - 105
EP - 123
JO - Neurocomputing
JF - Neurocomputing
SN - 0925-2312
ER -
ID: 32645896