PROJECT TITLE :

FFT-Based Spectrum Analysis in the Case of Data Loss

ABSTRACT:

The significance of measurement knowledge transfer over unreliable channel has emerged in the last decade, because of the spread of sensor networks and the concept of Internet of things. This paper investigates the behavior of the quick Fourier rework (FFT)-primarily based power spectral density (PSD) estimation in the case of information loss. There are different strategies accessible 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 knowledge loss models, and then offers some simple solutions on how the info loss can be handled in PSD estimation, when only moderate computing resources are out there. The potency of the proposed methodology is demonstrated by the simulation and measurement results.

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