Statistical data correction for unreliable memories

Christoph Roth; Christoph Studer; Georgios Karakonstantis; Andreas Burgi

doi:10.1109/ACSSC.2014.7094797

Statistical data correction for unreliable memories

Christoph Roth, Christoph Studer, Georgios Karakonstantis, Andreas Burgi

School of Electronics, Electrical Engineering and Computer Science

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

1 Citation (Scopus)

Abstract

In this paper, we introduce a statistical data-correction framework that aims at improving the DSP system performance in presence of unreliable memories. The proposed signal processing framework implements best-effort error mitigation for signals that are corrupted by defects in unreliable storage arrays using a statistical correction function extracted from the signal statistics, a data-corruption model, and an application-specific cost function. An application example to communication systems demonstrates the efficacy of the proposed approach.

Original language	English
Title of host publication	Conference Record - Asilomar Conference on Signals, Systems and Computers
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1890-1894
Number of pages	5
ISBN (Electronic)	9781479982974, ISSN: 1058-6393
ISBN (Print)	9781479982950
DOIs	https://doi.org/10.1109/ACSSC.2014.7094797
Publication status	Published - 24 Apr 2015
Event	48th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, United States Duration: 02 Nov 2014 → 05 Nov 2014

Conference

Conference	48th Asilomar Conference on Signals, Systems and Computers
Country/Territory	United States
City	Pacific Grove
Period	02/11/2014 → 05/11/2014

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing

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10.1109/ACSSC.2014.7094797

Cite this

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title = "Statistical data correction for unreliable memories",

abstract = "In this paper, we introduce a statistical data-correction framework that aims at improving the DSP system performance in presence of unreliable memories. The proposed signal processing framework implements best-effort error mitigation for signals that are corrupted by defects in unreliable storage arrays using a statistical correction function extracted from the signal statistics, a data-corruption model, and an application-specific cost function. An application example to communication systems demonstrates the efficacy of the proposed approach.",

author = "Christoph Roth and Christoph Studer and Georgios Karakonstantis and Andreas Burgi",

year = "2015",

month = apr,

day = "24",

doi = "10.1109/ACSSC.2014.7094797",

language = "English",

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pages = "1890--1894",

booktitle = "Conference Record - Asilomar Conference on Signals, Systems and Computers",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "48th Asilomar Conference on Signals, Systems and Computers ; Conference date: 02-11-2014 Through 05-11-2014",

}

Roth, C, Studer, C, Karakonstantis, G & Burgi, A 2015, Statistical data correction for unreliable memories. in Conference Record - Asilomar Conference on Signals, Systems and Computers., 7094797, Institute of Electrical and Electronics Engineers Inc., pp. 1890-1894, 48th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, United States, 02/11/2014. https://doi.org/10.1109/ACSSC.2014.7094797

Statistical data correction for unreliable memories. / Roth, Christoph; Studer, Christoph; Karakonstantis, Georgios et al.
Conference Record - Asilomar Conference on Signals, Systems and Computers. Institute of Electrical and Electronics Engineers Inc., 2015. p. 1890-1894 7094797.

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

TY - GEN

T1 - Statistical data correction for unreliable memories

AU - Roth, Christoph

AU - Studer, Christoph

AU - Karakonstantis, Georgios

AU - Burgi, Andreas

PY - 2015/4/24

Y1 - 2015/4/24

N2 - In this paper, we introduce a statistical data-correction framework that aims at improving the DSP system performance in presence of unreliable memories. The proposed signal processing framework implements best-effort error mitigation for signals that are corrupted by defects in unreliable storage arrays using a statistical correction function extracted from the signal statistics, a data-corruption model, and an application-specific cost function. An application example to communication systems demonstrates the efficacy of the proposed approach.

AB - In this paper, we introduce a statistical data-correction framework that aims at improving the DSP system performance in presence of unreliable memories. The proposed signal processing framework implements best-effort error mitigation for signals that are corrupted by defects in unreliable storage arrays using a statistical correction function extracted from the signal statistics, a data-corruption model, and an application-specific cost function. An application example to communication systems demonstrates the efficacy of the proposed approach.

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U2 - 10.1109/ACSSC.2014.7094797

DO - 10.1109/ACSSC.2014.7094797

M3 - Conference contribution

AN - SCOPUS:84940471542

SN - 9781479982950

SP - 1890

EP - 1894

BT - Conference Record - Asilomar Conference on Signals, Systems and Computers

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 48th Asilomar Conference on Signals, Systems and Computers

Y2 - 2 November 2014 through 5 November 2014

ER -

Statistical data correction for unreliable memories

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