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Chirp Code Deterministic Compressive Sensing: Analysis on Power Signal
Authors
Katia Melo, Mahdi Khosravy, Carlos Augusto Duque, Nilanjan Dey
Pages
125 - 134
DOI
10.3233/FAIA200053
Category
Research Article
SeriesEbook
Abstract

In the era of Internet of things and big data, a substantial problem in data transmission, processing, and storage is high data volume. In the case of harmonics, due to the high frequency contents, and the requirement by the Nyquist sampling theorem, short length data becomes impractical for efficient data transmission. Compressive sensing (CS) is a technique that comes to solve this problem deploying the sparsity of the signal to measure the signal with considerably fewer number of samples than the conventional methods. While most of CS techniques are via random sampling matrices, deterministic CS uses well-known matrices and deploy their characteristics. Deterministic CS by chirp codes is deterministic CS where this paper gives a detailed analysis to its technique and its implementation to power signal. The analysis includes the effect on deviations of the parameters of the harmonics, inter-harmonics, sub-harmonics.

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