Statistical data correction for unreliable memories
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Date
2015-04
Publication Type
Conference Paper
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yes
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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.
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Publication status
published
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Book title
2014 48th Asilomar Conference on Signals, Systems and Computers
Journal / series
Volume
Pages / Article No.
1890 - 1894
Publisher
IEEE
Event
48th Asilomar Conference on Signals, Systems and Computers (ACCESS 2014)