Blind identification of multi-input multi-output system using minimum noise subspace

This correspondence presents a ne iv subspace based method for blind identification of a p-input/q-output system, where q > p. This method exploits a minimum noise subspace (MNS) to retrieve the system impulse responses, The MNS method requires only q-p, noise vectors as opposed to all noise vectors needed by a standard subspace (SS) method, It is shown that the MNS can be obtained in a parallel structure from a set of tuples (combinations) of system outputs that form a properly connected sequence (PCS), The PCS exploits with minimum redundancy; the diversity among system outputs. The MNS method is much more efficient in computation than the SS method, although the former is less robust to noise thin the latter.