Stable algorithms for multiset canonical correlation analysis

This paper is devoted to the construction of dynamical systems that converge to principal subspaces of multi-set canonical variates using root objective functions. With some modifications, these systems may be converted to new ones that converge to the actual canonical variates. The main important features of two algorithms that have been tested are that the first algorithm converges to the canonical variates corresponding to the canonical correlations of largest magnitudes, while the other converges to the canonical variates corresponding to the largest positive canonical correlations.