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      A new OMP technique for sparse recovery

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      Author
      Teke, Oğuzhan
      Gürbüz, A.C.
      Arıkan, Orhan
      Date
      2012
      Source Title
      2012 20th Signal Processing and Communications Applications Conference (SIU)
      Publisher
      IEEE
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      Compressive Sensing (CS) theory details how a sparsely represented signal in a known basis can be reconstructed using less number of measurements. However in reality there is a mismatch between the assumed and the actual bases due to several reasons like discritization of the parameter space or model errors. Due to this mismatch, a sparse signal in the actual basis is definitely not sparse in the assumed basis and current sparse reconstruction algorithms suffer performance degradation. This paper presents a novel orthogonal matching pursuit algorithm that has a controlled perturbation mechanism on the basis vectors, decreasing the residual norm at each iteration. Superior performance of the proposed technique is shown in detailed simulations. © 2012 IEEE.
      Keywords
      Basis vector
      Compressive sensing
      Controlled perturbation
      Model errors
      Orthogonal matching pursuit
      Parameter spaces
      Performance degradation
      Residual norm
      Sparse reconstruction
      Sparse recovery
      Sparse signals
      Channel estimation
      Degradation
      Signal processing
      Permalink
      http://hdl.handle.net/11693/28196
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2012.6204606
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      • Department of Electrical and Electronics Engineering 3337

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