A growing neural gas network learns topologies

@incollection{citeulike:566805, abstract = {An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebb-like learning rule. In contrast to previous approaches like the \"neural gas\" method of Martinetz and Schulten (1991, 1994), this model has no parameters which change over time and is able to continue learning, adding units and connections, until a performance criterion has been met. Applications of the model include vector quantization,...}, address = {Cambridge MA}, author = {Fritzke, Bernd }, booktitle = {Advances in Neural Information Processing Systems 7}, citeulike-article-id = {566805}, editor = {Tesauro, G. and Touretzky, D. S. and Leen, T. K. }, keywords = {gas, growing, neural}, pages = {625--632}, posted-at = {2007-10-17 13:11:03}, priority = {2}, publisher = {MIT Press}, title = {A growing neural gas network learns topologies}, url = {http://citeseer.ist.psu.edu/fritzke95growing.html}, year = {1995} }

TY - CHAP ID - citeulike:566805 L3 - citeulike-article-id:566805 TI - A growing neural gas network learns topologies T2 - Advances in Neural Information Processing Systems 7 SP - 625 EP - 632 AD - Cambridge MA PB - MIT Press N2 - An incremental network model is introduced which is able to learn the important topological relations in a given set of input vectors by means of a simple Hebb-like learning rule. In contrast to previous approaches like the "neural gas" method of Martinetz and Schulten (1991, 1994), this model has no parameters which change over time and is able to continue learning, adding units and connections, until a performance criterion has been met. Applications of the model include vector quantization,... KW - gas KW - growing KW - neural AU - Fritzke, Bernd A2 - Tesauro, G A2 - Touretzky, DS A2 - Leen, TK PY - 1995/// UR - http://citeseer.ist.psu.edu/fritzke95growing.html ER -