Computational Complexity and Feasibility of Data Processing and Interval Computations , with Extension to Cases When We Have Partial Information about Probabilities

@inproceedings{Kreinovich2003ComputationalCA,
  title={Computational Complexity and Feasibility of Data Processing and Interval Computations , with Extension to Cases When We Have Partial Information about Probabilities},
  author={Vladik Kreinovich},
  year={2003}
}
In many real-life situations, we are interested in the value of a physical quantity y that is diicult or impossible to measure directly. To estimate y, we nd some easier-to-measure quantities x 1 ; : : : ; x n which are related to y by a known relation y = f (x 1 ; : : : ; x n). Measurements are never 100% accurate; hence, the measured values e x i are diierent from x i , and the resulting estimate e y = f (e x 1 ; : : : ; e x n) is diierent from the desired value y = f (x 1 ; : : : ; x n). How… CONTINUE READING
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