A geometric newton method for oja's vector field
Neural Computation
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This paper is concerned with the differential equation approximating the subspace learning algorithm for extracting principal components. Two issues are fully resolved. First, all the stable equilibria are found. Second, the global convergence rate is explicitly obtained. The whole treatment is without the nonsingularity assumption on the covariance matrix.