A square root sampling law for signal recovery

Mohammadi, E ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1109/LSP.2019.2899995
  3. Publisher: Institute of Electrical and Electronics Engineers Inc , 2019
  4. Abstract:
  5. The problem of finding the optimal node density for reconstructing a stochastic signal from its noisy samples in sensor networks is considered. The signal could be nonstationary and nonbandlimited. A weight is assigned to each location that indicates the relative importance of the signal at that location. It is shown that when the number of samples is very large, the optimal density of the samples at each location is proportional to the square root of the weight associated to that location
  6. Keywords:
  7. Distributed sampling ; Optimal sensor density ; Square root law ; Location ; Sensor networks ; Sensor nodes ; Stochastic systems ; Distributed samplings ; Nonstationary ; Number of samples ; Optimal densities ; Optimal sensor ; Signal recovery ; Square roots ; Stochastic signals ; Signal reconstruction
  8. Source: IEEE Signal Processing Letters ; Volume 26, Issue 4 , 2019 , Pages 562-566 ; 10709908 (ISSN)
  9. URL: https://ieeexplore.ieee.org/document/8643445