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Data Driven Sampling of Oscillating Signals

机译:数据驱动振荡信号采样

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摘要

The reduction of the number of samples is a key issue in signal processing for mobile applications. We investigate the link between the smoothness properties of a signal and the number of samples that can be obtained through a level crossing sampling procedure. The algorithm is analyzed and an upper bound of the number of samples is obtained in the worst case. The theoretical results are illustrated with applications to fractional Brownian motions and the Weierstrass function.
机译:样本数量的减少是移动应用的信号处理中的关键问题。我们研究了信号的平滑度属性与通过电平交叉采样过程可以获得的样本数之间的链路。分析算法,并在最坏的情况下获得样本数量的上限。理论结果被分支褐色动作和Weierstrass函数的应用说明。

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