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Aliasing-Truncation Errors in Sampling Approximations of Sub-Gaussian Signals

机译:次高斯信号采样近似中的混淆截断误差

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摘要

This paper starts with new aliasing-truncation error upper bounds in the sampling theorem for non-bandlimited stochastic signals. Then, it investigates Lp([0, T]) approximations of the sub-Gaussian random signals. Explicit truncation error upper bounds are established. The obtained rate of convergence provides a constructive algorithm for determining the sampling rate and the sample size in the truncated Whittaker-Kotel'nikovShannon expansions to ensure the approximation of the subGaussian signals with given accuracy and reliability. Some numerical examples are presented.
机译:本文从非带限随机信号的采样定理中的新的混叠截断误差上限开始。然后,它研究了次高斯随机信号的Lp([0,T])逼近。明确的截断误差上限已确定。所获得的收敛速率为确定截短的Whittaker-Kotel'nikovShannon展开中的采样率和样本大小提供了一个建设性算法,可确保以给定的精度和可靠性近似于高斯信号。给出了一些数值示例。

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