PARAFAC-Based Blind Estimation Of Possibly Underdetermined Convolutive MIMO Systems Export

@article{YuAndPetropulu2007, abstract = {In this paper, we consider the problem of blind identification of a convolutive multiple-input-multiple-output (MIMO) system with <i>No</i> outputs and <i>Ni</i> inputs. While many methods have been proposed to blindly identify convolutive MIMO systems with <i>No</i> ges <i>Ni</i> (overdetermined), very scarce results exist for the case of (underdetermined), all of which refer to systems that either have some special structure or special and values. In this paper, we show that, as long as , independent of whether the system is overdetermined or underdetermined, we can always find the appropriate order of statistics that guarantees identifiability of the system response within trivial ambiguities. We also propose an algorithm to reach the solution, that consists of parallel factorization (PARAFAC) of a -way tensor containing th-order statistics of the system outputs, followed by an iterative scheme. For a certain order of statistics , we provide the description of the class of identifiable MIMO systems. We also show that this class can be expanded by applying PARAFAC decomposition to a pair of tensors instead of one tensor. The proposed approach constitutes a novel scheme for estimation of underdetermined systems, and improves over existing approaches for overdetermined systems.}, author = {Yu, Yuanning and Petropulu, A. P.}, citeulike-article-id = {5998505}, citeulike-linkout-0 = {http://dx.doi.org/10.1109/TSP.2007.901148}, citeulike-linkout-1 = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4359530}, day = {18}, doi = {10.1109/TSP.2007.901148}, journal = {Signal Processing, IEEE Transactions on}, keywords = {bss, convolutive, ica, mimo, tensor}, month = {December}, number = {1}, pages = {111--124}, posted-at = {2009-10-23 21:02:30}, priority = {2}, title = {PARAFAC-Based Blind Estimation Of Possibly Underdetermined Convolutive MIMO Systems}, url = {http://dx.doi.org/10.1109/TSP.2007.901148}, volume = {56}, year = {2007} }

TY - JOUR ID - YuAndPetropulu2007 L3 - citeulike-article-id:5998505 N2 - In this paper, we consider the problem of blind identification of a convolutive multiple-input-multiple-output (MIMO) system with <i>No</i> outputs and <i>Ni</i> inputs. While many methods have been proposed to blindly identify convolutive MIMO systems with <i>No</i> ges <i>Ni</i> (overdetermined), very scarce results exist for the case of (underdetermined), all of which refer to systems that either have some special structure or special and values. In this paper, we show that, as long as , independent of whether the system is overdetermined or underdetermined, we can always find the appropriate order of statistics that guarantees identifiability of the system response within trivial ambiguities. We also propose an algorithm to reach the solution, that consists of parallel factorization (PARAFAC) of a -way tensor containing th-order statistics of the system outputs, followed by an iterative scheme. For a certain order of statistics , we provide the description of the class of identifiable MIMO systems. We also show that this class can be expanded by applying PARAFAC decomposition to a pair of tensors instead of one tensor. The proposed approach constitutes a novel scheme for estimation of underdetermined systems, and improves over existing approaches for overdetermined systems. IS - 1 JF - Signal Processing, IEEE Transactions on EP - 124 TI - PARAFAC-Based Blind Estimation Of Possibly Underdetermined Convolutive MIMO Systems VL - 56 SP - 111 KW - bss KW - convolutive KW - ica KW - mimo KW - tensor AU - Yu, Yuanning AU - Petropulu, AP PY - 2007/12/18/ UR - http://dx.doi.org/10.1109/TSP.2007.901148 ER -