An Extension of Neural Gas to Local PCA
Möller R, Hoffmann H (2004)
Neurocomputing 62: 305-326.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Möller, RalfUniBi
;
Hoffmann, Heiko
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Einrichtung
Abstract / Bemerkung
We suggest an extension of the neural gas vector quantization method to local principal component analysis. The distance measure for the competition between local units combines a normalized Mahalanobis distance in the principal subspace and the squared reconstruction error, with the weighting of both measures depending on the residual variance in the minor subspace. A recursive least-squares method performs the local principal component analysis. The method is tested on synthetic two- and three-dimensional data and on the recognition of handwritten digits. (C) 2004 Elsevier B.V. All rights reserved.
Stichworte
local principal component analysis;
handwritten digit recognition;
neural gas;
unsupervised learning;
quantization;
vector
Erscheinungsjahr
2004
Zeitschriftentitel
Neurocomputing
Band
62
Seite(n)
305-326
ISSN
0925-2312
Page URI
https://pub.uni-bielefeld.de/record/1937004
Zitieren
Möller R, Hoffmann H. An Extension of Neural Gas to Local PCA. Neurocomputing. 2004;62:305-326.
Möller, R., & Hoffmann, H. (2004). An Extension of Neural Gas to Local PCA. Neurocomputing, 62, 305-326. https://doi.org/10.1016/j.neucom.2003.09.014
Möller, Ralf, and Hoffmann, Heiko. 2004. “An Extension of Neural Gas to Local PCA”. Neurocomputing 62: 305-326.
Möller, R., and Hoffmann, H. (2004). An Extension of Neural Gas to Local PCA. Neurocomputing 62, 305-326.
Möller, R., & Hoffmann, H., 2004. An Extension of Neural Gas to Local PCA. Neurocomputing, 62, p 305-326.
R. Möller and H. Hoffmann, “An Extension of Neural Gas to Local PCA”, Neurocomputing, vol. 62, 2004, pp. 305-326.
Möller, R., Hoffmann, H.: An Extension of Neural Gas to Local PCA. Neurocomputing. 62, 305-326 (2004).
Möller, Ralf, and Hoffmann, Heiko. “An Extension of Neural Gas to Local PCA”. Neurocomputing 62 (2004): 305-326.
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