Wavelet kernel principal component analysis in noisy multiscale data classification

DOI10.5402/2012/197352zbMath1243.62085OpenAlexW2129683196WikidataQ58690112 ScholiaQ58690112MaRDI QIDQ442616

Anna T. Lawniczak, Shengkun Xie, Pietro Lio, Sridhar Krishnan

Publication date: 3 August 2012

Published in: ISRN Computational Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.5402/2012/197352

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40)

Related Items (1)

A gradient flow formulation for the stochastic Amari neural field model

Uses Software

• Kernlab

Cites Work

• Principal component analysis.
• Ten Lectures on Wavelets
• Flexible Discriminant Analysis by Optimal Scoring
• Kernel PCA for feature extraction and de-noising in nonlinear regression
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