An Extension of Neural Gas to Local PCA

Möller R, Hoffmann H (2004)
Neurocomputing 62: 305-326.

Journal Article | Published | English

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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.
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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.
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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