Modified Hebbian learning for curve and surface fitting
Neural Networks
Modified Oja's algorithms for principal subspace and minor subspace extraction
Neural Processing Letters
A minor subspace analysis algorithm
IEEE Transactions on Neural Networks
Global convergence of Oja's subspace algorithm for principal component extraction
IEEE Transactions on Neural Networks
Adaptive multiple minor directions extraction in parallel using a PCA neural network
Theoretical Computer Science
Incremental slow feature analysis
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Two
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Principal component analysis (PCA) and Minor component analysis (MCA) are similar but have different dynamical performances. Unexpectedly, a sequential extraction algorithm for MCA proposed by Luo and Unbehauen [11] does not work for MCA, while it works for PCA. We propose a different sequential-addition algorithm which works for MCA. We also show a conversion mechanism by which any PCA algorithms are converted to dynamically equivalent MCA algorithms and vice versa.