Ferdinand Peper, Hideki Noda. A symmetric linear neural network that learns principal components and their variances. IEEE Transactions on Neural Networks, 7(4):1042-1047, 1996. [doi]
@article{PeperN96-0,
title = {A symmetric linear neural network that learns principal components and their variances},
author = {Ferdinand Peper and Hideki Noda},
year = {1996},
doi = {10.1109/72.508948},
url = {http://dx.doi.org/10.1109/72.508948},
researchr = {https://researchr.org/publication/PeperN96-0},
cites = {0},
citedby = {0},
journal = {IEEE Transactions on Neural Networks},
volume = {7},
number = {4},
pages = {1042-1047},
}