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FFT-Based Spectrum Analysis in the Case of Data Loss

机译:数据丢失时基于FFT的频谱分析

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摘要

The significance of measurement data transfer over unreliable channel has emerged in the last decade, due to the spread of sensor networks and the idea of Internet of things. This paper investigates the behavior of the fast Fourier transform (FFT)-based power spectral density (PSD) estimation in the case of data loss. There are different methods available to estimate the PSD, but the hegemony of the FFT is beyond dispute, especially in real-time applications. This paper investigates the behavior of the PSD estimator in the case of different data loss models, and then offers some simple solutions on how the data loss can be handled in PSD estimation, when only moderate computing resources are available. The efficiency of the proposed method is demonstrated by the simulation and measurement results.
机译:在过去的十年中,由于传感器网络的普及和物联网的思想,测量数据在不可靠通道上传输的重要性已经显现。本文研究了在数据丢失的情况下基于快速傅里叶变换(FFT)的功率谱密度(PSD)估计的行为。有多种方法可以估算PSD,但是FFT的霸权性是无可争议的,尤其是在实时应用中。本文研究了在数据丢失模型不同的情况下PSD估计器的行为,然后提供了一些简单的解决方案,说明了在只有中等计算资源的情况下如何处理PSD估计中的数据丢失。仿真和测量结果证明了该方法的有效性。

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