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

Turev D. Acar; Athina P. Petropulu

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

Research output: Contribution to journal › Conference article › peer-review

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.

Original language	English (US)
Pages (from-to)	1080-1084
Number of pages	5
Journal	Conference Record of the Asilomar Conference on Signals, Systems and Computers
Volume	1
State	Published - 2003
Externally published	Yes
Event	Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: Nov 9 2003 → Nov 12 2003

All Science Journal Classification (ASJC) codes

Signal Processing
Computer Networks and Communications

Cite this

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title = "Blind MIMO system identification using PARAFAC decomposition of an output HOS-based tensor",

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.",

author = "Acar, {Turev D.} and Petropulu, {Athina P.}",

year = "2003",

language = "English (US)",

volume = "1",

pages = "1080--1084",

journal = "Conference Record of the Asilomar Conference on Signals, Systems and Computers",

issn = "1058-6393",

publisher = "IEEE Computer Society",

note = "Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers ; Conference date: 09-11-2003 Through 12-11-2003",

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TY - JOUR

T1 - Blind MIMO system identification using PARAFAC decomposition of an output HOS-based tensor

AU - Acar, Turev D.

AU - Petropulu, Athina P.

PY - 2003

Y1 - 2003

N2 - 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.

AB - 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.

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UR - http://www.scopus.com/inward/citedby.url?scp=4143062915&partnerID=8YFLogxK

M3 - Conference article

AN - SCOPUS:4143062915

SN - 1058-6393

VL - 1

SP - 1080

EP - 1084

JO - Conference Record of the Asilomar Conference on Signals, Systems and Computers

JF - Conference Record of the Asilomar Conference on Signals, Systems and Computers

T2 - Conference Record of the Thirty-Seventh Asilomar Conference on Signals, Systems and Computers

Y2 - 9 November 2003 through 12 November 2003

ER -

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

Abstract

All Science Journal Classification (ASJC) codes

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