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A modified Euclidean algorithm for isolating periodicities from a sparse set of noisy measurements

机译:改进的欧几里得算法,用于从稀疏的噪声测量集中隔离周期性

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A modified Euclidean algorithm is presented for determining the period from a sparse set of noisy measurements. The set may arise from measuring the occurrence time of noisy zero-crossings of a sinusoid with very many missing observations. The procedure is computationally simple, stable with respect to noise, and converges quickly. Its use is justified by a theorem that shows that, for a set of randomly chosen positive integers, the probability that they do not all share a common prime factor approaches one quickly as the cardinality of the set increases. Simulations are presented to demonstrate the proposed algorithm.
机译:提出了一种改进的欧几里得算法,用于根据稀疏的噪声测量集确定周期。该集合可能是由于测量正弦波有噪声的零交叉点的发生时间而导致的,其中有很多丢失的观测值。该过程计算简单,相对于噪声稳定,并且收敛迅速。它的使用由一个定理证明是正确的,该定理表明,对于一组随机选择的正整数,随着集合的基数增加,它们不都共享一个公质因数的概率将很快接近一个定理。仿真结果表明了该算法的有效性。

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