Blind MIMO system identification using PARAFAC decomposition of an output HOS-based tensor

Author

Acar, T.D. ; Petropulu, Athina P.

Author_Institution

Dept. of Electr. & Comput. Eng., Drexel Univ., Philadelphia, PA, USA

Volume

1

fYear

2003

fDate

9-12 Nov. 2003

Firstpage

1080

Abstract

We present a novel frequency domain approach for the identification of a multiple-input multiple-output (MIMO) system driven by white, mutually independent inputs. The system frequency response is obtained up to constant scaling and permutation ambiguities based on parallel factorization (PARAFAC) of a three-way tensor, which is constructed based on a higher-order statistics (HOS) of the system output. An important future of the proposed approach is that, unlike existing methods, no pre-whitening of the system outputs is needed, which translates to less estimation errors.

Keywords

MIMO systems; higher order statistics; identification; signal processing; tensors; HOS-based tensor; MIMO system; PARAFAC decomposition; estimation errors; frequency domain approach; higher-order statistics; multiple-input multiple-output system; parallel factorization; system output; three-way tensor; Biosensors; Frequency domain analysis; Frequency response; Higher order statistics; Independent component analysis; MIMO; Magnetic sensors; Speech processing; System identification; Tensile stress;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems and Computers, 2004. Conference Record of the Thirty-Seventh Asilomar Conference on

Print_ISBN

0-7803-8104-1

Type

conf

DOI

10.1109/ACSSC.2003.1292091

Filename

1292091