Subject: growing neural gas; faster convergence; fuzzy algorithm; non-stationary distribution;

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Year: 2009

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Type: Proceedings

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Title: Modified growing neural gas algorithm for faster convergence on signal distribution sudden change

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Author: Gancev, Stojancho
Author: Kulakov, Andrea

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Abstract: The paper deals with the problem of faster optimal coverage of a Growing Neural Gas algorithm for random signals appearing with non-stationary distributions. A modification of the algorithm that successfully solves this problem will be presented with simulations in a 2-D environment and statistical results that will show its efficiency. A comparison with a previous solution for the same problem using so called Utility measure will be also given.

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Publisher: IEEE

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Relation: 2009 XXII International Symposium on Information, Communication and Automation Technologies

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Identifier: oai:repository.ukim.mk:20.500.12188/24051
Identifier: http://hdl.handle.net/20.500.12188/24051

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