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- W1822676875 abstract "An efficient fault-detecting methodology, algorithm-based fault tolerance, may be extended to include error correction of the output data in a protected linear processing system by coupling a high-rate real convolutional code with a smoothed Kalman recursive estimation technique. A completely protected fault-tolerant linear processing system involving error correction is shown where it is guaranteed that no miscorrected data leave the configuration if at most one box-surrounded subsystem fails at a time. The real convolutional code dictates the comparable parity streams computed in two ways, forming the syndrome stream that is passed to the fixed-lag corrector when values exceed the threshold settings. The block processing and down sampling features of the convolutional code permit the overhead area to be from 20-50% of the main processing area." @default.
- W1822676875 created "2016-06-24" @default.
- W1822676875 creator A5022558902 @default.
- W1822676875 date "2002-11-19" @default.
- W1822676875 modified "2023-09-25" @default.
- W1822676875 title "Real number convolutional code correction and reliability calculations in fault-tolerant systems" @default.
- W1822676875 cites W1572575117 @default.
- W1822676875 doi "https://doi.org/10.1109/isit.1995.535736" @default.
- W1822676875 hasPublicationYear "2002" @default.
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