Abstract
A new bi-iteration type subspace tracker for updating a rank- r SVD approximant of a time-varying cross-correlation matrix of dimension N × M is introduced. The algorithm is based on updated orthonormal-square ( QS) decompositions with row-Householder reflections and attains a dominant complexity of 3 Nr + 3 Mr operations per time update, which is the lower bound of dominant complexity for an algorithm of this kind. A closed-form quasicode listing of the algorithm is provided. Computer experiments validate the theoretical results.
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