In this letter, we present a minor subspace rule that extracts the subspace that spans the m minor components of a n-dimensional vector stationary random process, m<n. The algorithm is self-stabilizing such that the subspace vectors do not need to be periodically normalized to unit modulus, and the algorithm does not require matrix inversions or divides toâ€¦Â (More)