Physical Sciences and Mathematics Commons^™

Efficient Algorithms For Synchroning Localization Sensors Under Interval Uncertainty, Raphael Voges, Bernardo Wagner, Vladik Kreinovich

Departmental Technical Reports (CS)

In this paper, we show that a practical need for synchronization of localization sensors leads to an interval-uncertainty problem. In principle, this problem can be solved by using the general linear programming algorithms, but this would take a long time -- and this time is not easy to decrease, e.g., by parallelization since linear programming is known to be provably hard to parallelize. To solve the corresponding problem, we propose more efficient and easy-to-parallelize algorithms.

How To Deal With Uncertainties In Computing: From Probabilistic And Interval Uncertainty To Combination Of Different Approaches, With Applications To Engineering And Bioinformatics, Vladik Kreinovich

Departmental Technical Reports (CS)

Most data processing techniques traditionally used in scientific and engineering practice are statistical. These techniques are based on the assumption that we know the probability distributions of measurement errors etc.

In practice, often, we do not know the distributions, we only know the bound D on the measurement accuracy -- hence, after the get the measurement result X, the only information that we have about the actual (unknown) value x of the measured quantity is that $x$ belongs to the interval [X − D, X + D]. Techniques for data processing under such interval uncertainty are called interval computations; these …