Efficient Sensing of Correlated Spatiotemporal Signals: A Stochastic Gradient Approach

Autor:	Alasti, Hadi
Rok vydání:	2019
Předmět:	Electrical Engineering and Systems Science - Signal Processing Electrical Engineering and Systems Science - Image and Video Processing
Druh dokumentu:	Working Paper
DOI:	10.1109/LSP.2019.2945125
Popis:	A significantly low cost and tractable progressive learning approach is proposed and discussed for efficient spatiotemporal monitoring of a completely unknown, two dimensional correlated signal distribution in localized wireless sensor field. The spatial distribution is compressed into a number of its contour lines and only those sensors that their sensor observations are in a $\Delta$ margin of the contour levels are reporting to the information fusion center (IFC). The proposed algorithm progressively finds the model parameters in iterations, by using extrapolation in curve fitting, and stochastic gradient method for spatial monitoring. The IFC tracks the signal variations using these parameters, over time. The monitoring performance and the cost of the proposed algorithm are discussed, in this letter. Comment: 5 pages, 7 figures, article
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1908.07674 Zobrazit plný text záznamu View this record from Arxiv