Error estimation for the results of signal processing is traditionally based on the assumption that we know the probability distribution of the input signals. In many real-life situations, however, we only know the upper bounds for the signal's error, i.e., we only know the intervals of possible values of the input signal. In such situations, we are interested in knowing the interval of possible values of the output. The corresponding computations are often very computationally intensive; in this paper, we describe a special purpose hardware which can drastically speed up the computation of interval estimates for signal processing.
Reliable Computing – Springer Journals
Published: Sep 30, 2004
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