Now showing items 1-20 of 24

    • Accelerated phase-cycled SSFP imaging with compressed sensing 

      Çukur, T. (Institute of Electrical and Electronics Engineers Inc., 2015)
      Balanced steady-state free precession (SSFP) imaging suffers from irrecoverable signal losses, known as banding artifacts, in regions of large B0 field inhomogeneity. A common solution is to acquire multiple phase-cycled ...
    • Average error in recovery of sparse signals and discrete fourier transform 

      Özçelikkale, Ayça; Yüksel, S.; Özaktaş Haldun M. (IEEE, 2012-04)
      In compressive sensing framework it has been shown that a sparse signal can be successfully recovered from a few random measurements. The Discrete Fourier Transform (DFT) is one of the transforms that provide the best ...
    • Compressed sensing on ambiguity function domain for high resolution detection 

      Güldoǧan, Mehmet B.; Pilancı, Mert; Arıkan, Orhan (IEEE, 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 ...
    • A compression method for 3-D laser range scans of indoor environments based on compressive sensing 

      Dobrucalı, Oğuzcan; Barshan, Biilur (IEEE, 2011-08-09)
      Modeling and representing 3-D environments require the transmission and storage of vast amount of measurements that need to be compressed efficiently. We propose a novel compression technique based on compressive sensing ...
    • Compressive sampling and adaptive multipath estimation 

      Pilancı, Mert; Arıkan, Orhan (IEEE, 2010)
      In many signal processing problems such as channel estimation and equalization, the problem reduces to a linear system of equations. In this proceeding we formulate and investigate linear equations systems with sparse ...
    • Compressive sensing based flame detection in infrared videos 

      Günay, Osman; Çetin, A. Enis (IEEE, 2013)
      In this paper, a Compressive Sensing based feature extraction algorithm is proposed for flame detection using infrared cameras. First, bright and moving regions in videos are detected. Then the videos are divided into ...
    • Compressive sensing based target detection in delay-doppler radars 

      Teke, Oguzhan; Arıkan, Orhan; Gürbüz, A.C. (IEEE, 2013)
      Compressive Sensing theory shows that, a sparse signal can be reconstructed from its sub-Nyquist rate random samples. With this property, CS approach has many applications. Radar systems, which deal with sparse signal due ...
    • Compressive sensing imaging with a graphene modulator at THz frequency in transmission mode 

      Özkan, V. A.; Takan, T.; Kakenov, Nurbek; Kocabaş, Coşkun; Altan, H. (IEEE, 2016)
      In this study we demonstrate compressive sensing imaging with a unique graphene based optoelectronic device which allows us to modulate the THz field through an array of columns or rows distributed throughout its face.
    • Detection of sparse targets with structurally perturbed echo dictionaries 

      Guldogan, M. B.; Arikan, O. (Elsevier, 2013)
      In this paper, a novel algorithm is proposed to achieve robust high resolution detection in sparse multipath channels. Currently used sparse reconstruction techniques are not immediately applicable in multipath channel ...
    • Ellipsoid genişletmeyle seyrek sinyal geri oluşturma 

      Gürbüz, A. C.; Pilancı, M.; Arıkan, Orhan (IEEE, 2011-04)
      Bu makalede b = Ax + n şeklinde gürültülü A’nın tam rank ve x’in seyrek olduğu doğrusal bir denklem sistemi için seyrek x sinyallerini doğru olarak geri oluşturmaya yönelik yeni bir yöntem sunulmuştur. Önerilen yöntem ...
    • An empirical eigenvalue-threshold test for sparsity level estimation from compressed measurements 

      Lavrenko, A.; Römer, F.; Del Galdo, G.; Thoma, R.; Arıkan, Orhan (IEEE, 2014)
      Compressed sensing allows for a significant reduction of the number of measurements when the signal of interest is of a sparse nature. Most computationally efficient algorithms for signal recovery rely on some knowledge ...
    • Image feature extraction using compressive sensing 

      Eleyan, A.; Köse, Kıvanç; Çetin, Ahmet Enis (Springer, 2014)
      In this paper a new approach for image feature extraction is presented. We used the Compressive Sensing (CS) concept to generate the measurement matrix. The new measurement matrix is different from the measurement matrices ...
    • Performance assessment of a diffraction field computation method based on source model 

      Esmer, G. Bora; Onural, Levent; Özaktaş, Haldun M.; Uzunov, V.; Gotchev, A. (IEEE, 2008-05)
      Efficient computation of scalar optical diffraction field due to an object is an essential issue in holographic 3D television systems. The first step in the computation process is to construct an object. As a solution for ...
    • 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 ...
    • Polar compressive sampling: A novel technique using polar codes 

      Pilancı, Mert; Arıkan, Orhan; Arıkan, Erdal (IEEE, 2010)
      Recently introduced Polar coding is the first practical coding technique that can be proven to achieve the Shannon capacity for a multitude of communication channels. Polar codes are close to Reed-Muller codes except the ...
    • Range-doppler radar target detection using denoising within the compressive sensing framework 

      Sevimli, R. Akın; Tofighi, Mohammad; Çetin, A. Enis (IEEE, 2014-09)
      Compressive sensing (CS) idea enables the reconstruction of a sparse signal from a small set of measurements. CS approach has applications in many practical areas. One of the areas is radar systems. In this article, the ...
    • Recovery of sparse perturbations in Least Squares problems 

      Pilanci, M.; Arıkan, Orhan (IEEE, 2011)
      We show that the exact recovery of sparse perturbations on the coefficient matrix in overdetermined Least Squares problems is possible for a large class of perturbation structures. The well established theory of Compressed ...
    • Seyrek sinyallerin geri çatımına özyineli bir yaklaşım 

      Teke, Oğuzhan; Arıkan, Orhan; Gürbüz, A. C. (IEEE, 2014-04)
      Sıkıştırılmış Algılama (SA) kuramı, bilinen bir tabanda seyrek olan bir sinyalin az sayıda ölçüm ile nasıl geri çatılacağını inceler. Çoğu pratik sistemdeki ölçüm sinyallerinin sürekli bir parametre uzayında seyrek bir ...
    • Sparsity order estimation for single snapshot compressed sensing 

      Romer, F.; Lavrenko, A.; Del Galdo, G.; Hotz, T.; Arıkan, Orhan; Thoma, R. S. (IEEE, 2015-11)
      In this paper we discuss the estimation of the spar-sity order for a Compressed Sensing scenario where only a single snapshot is available. We demonstrate that a specific design of the sensing matrix based on Khatri-Rao ...
    • Sub-band equalization of modulated wideband converter for improved dynamic range performance 

      Korucu, A. B.; Alp, Y. K.; Gök, Gökhan; Arıkan, Orhan (IEEE, 2017)
      In this work, we propose a new method to improve the dynamic range performance of the Modulated Wideband Converter (MWC), which is multi-channel sampling system for digitizing wideband sparse signals below the Nyquist limit ...