Recursive estimation for ordered eigenvectors of symmetric matrix with observation noise
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Publication:549818
DOI10.1016/j.jmaa.2011.04.072zbMath1217.62085OpenAlexW2087767175MaRDI QIDQ549818
Li-Li Zhang, Hai-Tao Fang, Chen, Hanfu
Publication date: 18 July 2011
Published in: Journal of Mathematical Analysis and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.jmaa.2011.04.072
stochastic approximationconvergence raterecursive algorithmprincipal component analysis (PCA)ordered convergence
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Cites Work
- On stochastic approximation of the eigenvectors and eigenvalues of the expectation of a random matrix
- Convergence of algorithms used for principal component analysis
- Stochastic approximation and its applications
- Do stochastic algorithms avoid traps?
- Some Pathological Traps for Stochastic Approximation
- General results on the convergence of stochastic algorithms
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