A continuous-time Hebbian/anti-Hebbian similarity matching network is shown to converge layer by layer to the principal subspace solution, with the slow layer convergence relying on two unproven conjectures.
Bullo.Contraction Theory for Dynamical Systems
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Similarity Matching Networks: Hebbian Learning and Convergence Over Multiple Time Scales
A continuous-time Hebbian/anti-Hebbian similarity matching network is shown to converge layer by layer to the principal subspace solution, with the slow layer convergence relying on two unproven conjectures.