Now showing items 1-8 of 8

    • Coded scenes for fast system calibration in magnetic particle imaging 

      Ilbey, S.; Top, C. B.; Güngör, A.; Saritas, E. U.; Güven, E. (Institute of Electrical and Electronics Engineers, 2018)
      Magnetic nanoparticle (MNP) agents have a wide range of clinical application areas for both imaging and therapy. MNP distribution inside the body can be imaged using Magnetic Particle Imaging (MPI). For MPI image reconstruction ...
    • Compressed sensing on ambiguity function domain for high resolution detection 

      Güldoǧan, M.B.; Pilanci, M.; Arikan, O. (2010)
      In this paper, by using compressed sensing techniques, a new approach to achieve robust high resolution detection in sparse multipath channels is presented. Currently used sparse reconstruction techniques are not immediately ...
    • Expectation maximization based matching pursuit 

      Gurbuz, A.C.; Pilanci, M.; Arikan, O. (2012)
      A novel expectation maximization based matching pursuit (EMMP) algorithm is presented. The method uses the measurements as the incomplete data and obtain the complete data which corresponds to the sparse solution using an ...
    • A new OMP technique for sparse recovery 

      Teke, Oğuzhan; Gürbüz, A.C.; Arıkan, Orhan (IEEE, 2012)
      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 ...
    • Perturbed orthogonal matching pursuit 

      Teke, O.; Gurbuz, A. C.; Arikan, O. (IEEE, 2013)
      Compressive Sensing theory details how a sparsely represented signal in a known basis can be reconstructed with an underdetermined linear measurement model. However, in reality there is a mismatch between the assumed and ...
    • A recursive way for sparse reconstruction of parametric spaces 

      Teke O.; Gurbuz, A.C.; Arikan, O. (IEEE Computer Society, 2015)
      A novel recursive framework for sparse reconstruction of continuous parameter spaces is proposed by adaptive partitioning and discretization of the parameter space together with expectation maximization type iterations. ...
    • Sparse delay-Doppler image reconstruction under off-grid problem 

      Teke O.; Gurbuz, A.C.; Arikan, O. (IEEE Computer Society, 2014)
      Pulse-Doppler radar has been successfully applied to surveillance and tracking of both moving and stationary targets. For efficient processing of radar returns, delay-Doppler plane is discretized and FFT techniques are ...
    • Sparse ground-penetrating radar imaging method for off-the-grid target problem 

      Gurbuz, A. C.; Teke, O.; Arikan, O. (SPIE, 2013)
      Spatial sparsity of the target space in subsurface or through-the-wall imaging applications has been successfully used within the compressive-sensing framework to decrease the data acquisition load in practical systems, ...