Weight-Value Convergence of the SOM Algorithm for Discrete Input

Some insights on the convergence of the weight values of the self-organizing map (SOM) to a stationary state in the case of discrete input are provided. The convergence result is obtained by applying the Robbins-Monro algorithm and is applicable to input-output maps of any dimension.

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Bibliographische Detailangaben
Veröffentlicht in:	Neural computation 1998-05, Vol.10 (4), p.807-814
Hauptverfasser:	Lin, Siming, Si, Jennie
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Artificial intelligence Brain Mapping Computer science control theory systems Exact sciences and technology Image Processing, Computer-Assisted Mathematics Problem solving, game playing Regression Analysis Theoretical computing
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Beschreibung
Zusammenfassung:	Some insights on the convergence of the weight values of the self-organizing map (SOM) to a stationary state in the case of discrete input are provided. The convergence result is obtained by applying the Robbins-Monro algorithm and is applicable to input-output maps of any dimension.
ISSN:	0899-7667 1530-888X
DOI:	10.1162/089976698300017485