TY - GEN
T1 - Design and Analysis of Neural Networks Based on Linearly Translated Features
AU - Wang, Jiasen
AU - Wang, Jun
AU - Zhang, Wei
PY - 2019/12
Y1 - 2019/12
N2 - In this paper, neural networks based on linearly translated features (LTFs) are presented. LTFs including uniform, non-uniform, and multiple translation vectors are embedded into feedforward neural networks. Learning algorithms are presented for the neural networks. Learning capabilities of the neural networks are analyzed. Experimental results on approximation' identification, and evaluation problems are reported to substantiate the efficacy of the neural networks and learning algorithms.
AB - In this paper, neural networks based on linearly translated features (LTFs) are presented. LTFs including uniform, non-uniform, and multiple translation vectors are embedded into feedforward neural networks. Learning algorithms are presented for the neural networks. Learning capabilities of the neural networks are analyzed. Experimental results on approximation' identification, and evaluation problems are reported to substantiate the efficacy of the neural networks and learning algorithms.
KW - linearly translated features
KW - Neural networks
KW - linearly translated features
KW - Neural networks
KW - linearly translated features
KW - Neural networks
UR - http://www.scopus.com/inward/record.url?scp=85082240288&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85082240288&origin=recordpage
U2 - 10.1109/ICICIP47338.2019.9012159
DO - 10.1109/ICICIP47338.2019.9012159
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9781728100166
T3 - International Conference on Intelligent Control and Information Processing, ICICIP
SP - 289
EP - 296
BT - 10th International Conference on Intelligent Control and Information Processing (ICICIP)
PB - IEEE
T2 - 10th International Conference on Intelligent Control and Information Processing (ICICIP 2019)
Y2 - 14 December 2019 through 19 December 2019
ER -