The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data

Stefano Fortunati; Maria S. Greco; Fulvio Gini

doi:10.1109/SSP.2016.7551738

The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data

Stefano Fortunati, Maria S. Greco, Fulvio Gini

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Scatter matrix estimation and hypothesis testing in Complex Elliptically Symmetric (CES) distributions often relies on the knowledge of additional parameters characterizing the distribution at hand. In this paper, we investigate the performance of optimal estimation and detection algorithms exploiting low-complexity but suboptimal estimates of the extra parameters under the assumption of t-distributed data. Their performance is also compared with that of robust algorithms, which do not rely on such estimates.

Original language	English
Title of host publication	2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016
Publisher	IEEE Computer Society
ISBN (Electronic)	9781467378024
DOIs	https://doi.org/10.1109/SSP.2016.7551738
Publication status	Published - 24 Aug 2016
Externally published	Yes
Event	19th IEEE Statistical Signal Processing Workshop, SSP 2016 - Palma de Mallorca, Spain Duration: 25 Jun 2016 → 29 Jun 2016

Publication series

Name	IEEE Workshop on Statistical Signal Processing Proceedings
Volume	2016-August

Conference

Conference	19th IEEE Statistical Signal Processing Workshop, SSP 2016
Country/Territory	Spain
City	Palma de Mallorca
Period	25/06/16 → 29/06/16

Keywords

Linear Threshold Detector
Maximum Likelihood
Method of Moments
Normalized Matched Filter

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10.1109/SSP.2016.7551738

Cite this

Fortunati, S., Greco, M. S., & Gini, F. (2016). The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data. In 2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016 Article 7551738 (IEEE Workshop on Statistical Signal Processing Proceedings; Vol. 2016-August). IEEE Computer Society. https://doi.org/10.1109/SSP.2016.7551738

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title = "The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data",

abstract = "Scatter matrix estimation and hypothesis testing in Complex Elliptically Symmetric (CES) distributions often relies on the knowledge of additional parameters characterizing the distribution at hand. In this paper, we investigate the performance of optimal estimation and detection algorithms exploiting low-complexity but suboptimal estimates of the extra parameters under the assumption of t-distributed data. Their performance is also compared with that of robust algorithms, which do not rely on such estimates.",

keywords = "Linear Threshold Detector, Maximum Likelihood, Method of Moments, Normalized Matched Filter",

author = "Stefano Fortunati and Greco, \{Maria S.\} and Fulvio Gini",

note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 19th IEEE Statistical Signal Processing Workshop, SSP 2016 ; Conference date: 25-06-2016 Through 29-06-2016",

year = "2016",

month = aug,

day = "24",

doi = "10.1109/SSP.2016.7551738",

language = "English",

series = "IEEE Workshop on Statistical Signal Processing Proceedings",

publisher = "IEEE Computer Society",

booktitle = "2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016",

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Fortunati, S, Greco, MS & Gini, F 2016, The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data. in 2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016., 7551738, IEEE Workshop on Statistical Signal Processing Proceedings, vol. 2016-August, IEEE Computer Society, 19th IEEE Statistical Signal Processing Workshop, SSP 2016, Palma de Mallorca, Spain, 25/06/16. https://doi.org/10.1109/SSP.2016.7551738

The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data. / Fortunati, Stefano; Greco, Maria S.; Gini, Fulvio.
2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016. IEEE Computer Society, 2016. 7551738 (IEEE Workshop on Statistical Signal Processing Proceedings; Vol. 2016-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Greco, Maria S.

AU - Gini, Fulvio

PY - 2016/8/24

Y1 - 2016/8/24

N2 - Scatter matrix estimation and hypothesis testing in Complex Elliptically Symmetric (CES) distributions often relies on the knowledge of additional parameters characterizing the distribution at hand. In this paper, we investigate the performance of optimal estimation and detection algorithms exploiting low-complexity but suboptimal estimates of the extra parameters under the assumption of t-distributed data. Their performance is also compared with that of robust algorithms, which do not rely on such estimates.

AB - Scatter matrix estimation and hypothesis testing in Complex Elliptically Symmetric (CES) distributions often relies on the knowledge of additional parameters characterizing the distribution at hand. In this paper, we investigate the performance of optimal estimation and detection algorithms exploiting low-complexity but suboptimal estimates of the extra parameters under the assumption of t-distributed data. Their performance is also compared with that of robust algorithms, which do not rely on such estimates.

KW - Linear Threshold Detector

KW - Maximum Likelihood

KW - Method of Moments

KW - Normalized Matched Filter

UR - https://www.scopus.com/pages/publications/84987916804

U2 - 10.1109/SSP.2016.7551738

DO - 10.1109/SSP.2016.7551738

M3 - Conference contribution

AN - SCOPUS:84987916804

T3 - IEEE Workshop on Statistical Signal Processing Proceedings

BT - 2016 19th IEEE Statistical Signal Processing Workshop, SSP 2016

PB - IEEE Computer Society

T2 - 19th IEEE Statistical Signal Processing Workshop, SSP 2016

Y2 - 25 June 2016 through 29 June 2016

ER -

The impact of unknown extra parameters on scatter matrix estimation and detection performance in complex t-distributed data

Abstract

Publication series

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Keywords

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