# Show Reference: "A Growing Neural Gas Network Learns Topologies"

A Growing Neural Gas Network Learns Topologies In Advances in Neural Information Processing Systems 7 (1995), pp. 625-632 by Bernd Fritzke edited by Gerald Tesauro, David S. Touretzky, Todd K. Leen
@incollection{fritzke-1995,
abstract = {An incremental network model is introduced which is able to learnthe important topological relations in a given set of input vectors bymeans of a simple Hebb-like learning rule. In contrast to previousapproaches like the "neural gas" method of Martinetz and Schulten(1991, 1994), this model has no parameters which change over timeand is able to continue learning, adding units and connections, untila performance criterion has been met. Applications of the modelinclude vector quantization,...},
author = {Fritzke, Bernd},
booktitle = {Advances in Neural Information Processing Systems 7},
citeulike-article-id = {566805},
editor = {Tesauro, Gerald and Touretzky, David S. and Leen, Todd K.},
keywords = {ann, growing-neural-gas, learning, som, topology, unsupervised-learning},
pages = {625--632},
posted-at = {2014-12-19 15:12:09},
priority = {2},
publisher = {MIT Press},
title = {A Growing Neural Gas Network Learns Topologies},
url = {http://web.cs.swarthmore.edu/\~{}meeden/DevelopmentalRobotics/fritzke95.pdf},
year = {1995}
}