@inbook{8950c0e9091e450fab3158637a68aff4,

title = "Blind MIMO identification using the second characteristic function",

abstract = "We propose a novel algorithm for the identification of a Multi-Input-Multi-Output (MIMO) system. Instead of using {"}classical{"} high-order statistics, the mixing system is estimated directly from the empirical Hessian matrices of the second generalized characteristic function (GCF) at several preselected {"}processing points{"}. An approximate joint-diagonalization scheme is applied to the transformed set of matrices in the frequency domain. This yields a set of estimated frequency response matrices, which are transformed back into the time domain after resolving frequency-dependent phase and permutation ambiguities. The algorithm's performance depends on the choice of processing points, yet compares favorably with other algorithms, especially at moderate SNR conditions.",

author = "Eran Eidinger and Arie Yeredor",

year = "2004",

doi = "10.1007/978-3-540-30110-3_73",

language = "אנגלית",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "570--577",

editor = "Puntonet, {Carlos G.} and Alberto Prieto",

booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}