Adaptive blind MIMO system identification using principal component neural models

We treat the blind identification problem for a n×n MIMO system using second order frequency-domain statistics and asymmetric PCA neural models. It is assumed that the source signals are colored, stationary, and pair-wise independent sequences with otherwise unknown statistics. We introduce a set of invariant indices that are used to tackle the problem of frequency-dependent ambiguities in the ordering and the phase of the retrieved singular vectors. For the case of 2×2 systems we present a complete identification procedure based on the corresponding invariant indices and we conjecture that these indices can be instrumental in the solution of the general n×n problem as well