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      Optimal representation of non-stationary random fields with finite numbers of samples: A linear MMSE framework

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      Author
      Özçelikkale, A.
      Haldun M. Özaktaş
      Date
      2013
      Source Title
      Digital Signal Processing: A Review Journal
      Print ISSN
      1051-2004
      Publisher
      Elsevier
      Volume
      23
      Issue
      5
      Pages
      1602 - 1609
      Language
      English
      Type
      Article
      Item Usage Stats
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      Abstract
      In this article we consider the representation of a finite-energy non-stationary random field with a finite number of samples. We pose the problem as an optimal sampling problem where we seek the optimal sampling interval under the mean-square error criterion, for a given number of samples. We investigate the optimum sampling rates and the resulting trade-offs between the number of samples and the representation error. In our numerical experiments, we consider a parametric non-stationary field model, the Gaussian-Schell model, and present sampling schemes for varying noise levels and for sources with varying numbers of degrees of freedom. We discuss the dependence of the optimum sampling interval on the problem parameters. We also study the sensitivity of the error to the chosen sampling interval.
      Keywords
      Gaussian-Schell model
      Non-stationary signals
      Random field estimation
      Uniform sampling
      Gaussian-schell models
      Nonstationary signals
      Numerical experiments
      Optimum samplings
      Problem parameters
      Random fields
      Sampling interval
      Uniform sampling
      Digital signal processing
      Optimization
      Permalink
      http://hdl.handle.net/11693/20833
      Published Version (Please cite this version)
      http://dx.doi.org/10.1016/j.dsp.2013.05.001
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      • Department of Electrical and Electronics Engineering 3524
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