A comparative investigation on subspace dimension determination

DOI10.1016/J.NEUNET.2004.07.005zbMath1079.68590DBLPjournals/nn/HuX04OpenAlexW2024262632WikidataQ51578539 ScholiaQ51578539MaRDI QIDQ2485228

Xuelei Hu

Publication date: 3 August 2005

Published in: Neural Networks (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.neunet.2004.07.005

zbMATH Keywords

Principal component analysisModel selectionBYY harmony learningData smoothingSubspace dimension

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Uses Software

• LAPACK

Cites Work

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• Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
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• Estimating the dimension of a model
• Principal component analysis.
• A second generation little Jiffy
• Temporal BYY learning for state space approach, hidden Markov model, and blind source separation
• The minimum description length principle in coding and modeling
• VI.—The Estimation of Factor Loadings by the Method of Maximum Likelihood
• A new look at the statistical model identification

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