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New algorithms for the exact computation of the sign of algebraic expressions

机译:精确计算代数表达式符号的新算法

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The paper considers the problem of exact computation of the sign of algebraic expressions of real numbers represented in floating point arithmetic. We describe a new method for the exact computation and suggest some variations to improve the efficiency. The input data for the algorithm is represented by normalized floating point numbers with fixed mantissa length (machine numbers). The algorithm computes the exact value of the sign of the sum of machine numbers and it can be applied to exactly compute the sign of almost any algebraic expression. We suggest several variations of the original Exact Sign of a Sum Algorithm (ESSA) to improve the performance of the algorithm and we test the algorithms on different data sets. This includes the implementation of floating point filters based on interval analysis, a special algorithm for performing multiple bit-wise transformations on the numbers in lists and the application of different rules to reduce the number of iterations of the algorithm. The theoretical upper bound on the complexity of ESSA is O(l/sup 2/), where l is the number of elements of the input. The expected average, experimental complexity of the suggested algorithms is proportional to the length of the input lists and it is close to l/2 in most cases. We perform a comparison analysis among the algorithms. The comparisons are based on the computational efficiency of the algorithms on both well posed and ill posed data sets. The algorithms are verified by the computer implementations.
机译:本文考虑了浮点运算中实数的代数表达式的符号的精确计算问题。我们描述了一种用于精确计算的新方法,并提出了一些改进方法以提高效率。该算法的输入数据由具有固定尾数长度(机器编号)的标准化浮点数表示。该算法计算出机器数之和的正负号的精确值,并且可以应用于精确计算几乎任何代数表达式的正负号。我们提出了求和算法(ESSA)的原始精确符号的几种变体,以提高算法的性能,并在不同的数据集上对算法进行测试。这包括基于间隔分析的浮点滤波器的实现,一种用于对列表中的数字执行多个按位转换的特殊算法,以及应用不同的规则来减少算法的迭代次数。 ESSA复杂度的理论上限是O(l / sup 2 /),其中l是输入元素的数量。所建议算法的预期平均实验复杂度与输入列表的长度成正比,在大多数情况下,其接近l / 2。我们在算法之间进行比较分析。比较是基于算法在适当状态和不良状态数据集上的计算效率。该算法已通过计算机实现进行了验证。

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