Now showing items 1-19 of 19

    • 3D electron density estimation in the ionosphere 

      Tuna, Hakan; Arıkan, Orhan; Arıkan, F. (IEEE, 2014)
      Ionosphere has ion distribution which is variable in space and time. There have been physical and empirical studies for modeling the ionosphere. International Reference Ionosphere extended to Plasmasphere (IRI-Plas) is the ...
    • The COST292 experimental framework for TRECVID 2007 

      Zhang, Q.; Corvaglia, M.; Aksoy, Selim; Naci, U.; Adami, N.; Aginako, N.; Alatan, A.; Alexandre, L. A.; Almeida, P.; Avrithis, Y.; Benois-Pineau, J.; Chandramouli, K.; Damnjanovic, U.; Esen, E.; Goya, J.; Grzegorzek, M.; Hanjalic, A.; Izquierdo, E.; Jarina, R.; Kapsalas, P.; Kompatsiaris, I.; Kuba, M.; Leonardi, R.; Makris, L.; Mansencal, B.; Mezaris, V.; Moumtzidou, A.; Mylonas, P.; Nikolopoulos, S.; Piatrik, T.; Pinheiro, A. M. G.; Reljin, B.; Spyrou, E.; Tolias, G.; Vrochidis, S.; Yakın, G.; Zajic, G. (National Institute of Standards and Technology, 2007)
      In this paper, we give an overview of the four tasks submitted to TRECVID 2007 by COST292. In shot boundary (SB) detection task, four SB detectors have been developed and the results are merged using two merging algorithms. ...
    • 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 ...
    • Dipole source reconstruction of brain signals by using particle swarm optimization 

      Alp, Yaşar Kemal; Arıkan, Orhan; Karakaş, S. (IEEE, 2009)
      Resolving the sources of neural activity is of prime importance in the analysis of Event Related Potentials (ERP). These sources can be modeled as effective dipoles. Identifying the dipole parameters from the measured ...
    • Distributed detection by Particle Swarm Optimization 

      Ince O.; Efe, M.; Arikan, O. (2011)
      Nature inspired optimization methods have been finding many application areas in different disciplines due to their ease of use and high performance. In this study, Particle Swarm Optimization, a nature inspired optimization ...
    • ERP source reconstruction by using Particle Swarm Optimization 

      Alp, Yaşar Kemal; Arıkan, Orhan; Karakaş, S. (IEEE, 2009)
      Localization of the sources of Event Related Potentials (ERP) is a challenging inverse problem, especially to resolve sources of neural activity occurring simultaneously. By using an effective dipole source model, we propose ...
    • Maximum likelihood estimation of Gaussian mixture models using particle swarm optimization 

      Arı, Çağlar; Aksoy, Selim (IEEE, 2010-08)
      We present solutions to two problems that prevent the effective use of population-based algorithms in clustering problems. The first solution presents a new representation for arbitrary covariance matrices that allows ...
    • Multipath channel identification by using global optimization in ambiguity function domain 

      Guldogan, M. B.; Arikan, O. (ELSEVIER, 2011-06-15)
      A new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delayDoppler domain by using the cross-ambiguity ...
    • Optimal stochastic signaling for power-constrained binary communications systems 

      Goken, C.; Gezici, S.; Arikan, O. (IEEE, 2010)
      Optimal stochastic signaling is studied under second and fourth moment constraints for the detection of scalar-valued binary signals in additive noise channels. Sufficient conditions are obtained to specify when the use ...
    • Parameter estimation for synthetic TEC surfaces by using Particle Swarm Optimization 

      Gökdaǧ, Y.E.; Arikan F.; Toker, C.; Arıkan, Orhan (IEEE, 2012)
      In this study, parameter estimation is made for global ionospheric Total Electron Content (TEC) on both noiseless and noisy synthetic surfaces by using modified Particle Swarm Optimization (PSO). In addition, the improvements ...
    • Particle swarm optimization based channel identification in cross-ambiguity domain 

      Güldoğan, Mehmet Burak; Arıkan, Orhan (IEEE, 2010)
      In this paper, a new array signal processing technique by using particle swarm optimization (PSO) is proposed to identify multipath channel parameters. The proposed technique provides estimates to the channel parameters ...
    • A particle swarm optimization based SAR motion compensation algorithm for target image reconstruction 

      Uğur, Salih; Arıkan, Orhan (IEEE, 2010)
      A new SAR motion compensation algorithm is proposed for robust reconstruction of target images even under large deviations of the platform from intended flight path. Phase error due to flight path deviations is estimated ...
    • Particle swarm optimization for SAGE maximization step in channel parameter estimation 

      Bodur, Harun; Tunç, Celal Alp; Aktaş, Defne; Ertürk, Vakur .B.; Altıntaş, Ayhan (IET, 2007-11)
      This paper presents an application of particle swarm optimization (PSO) in space alternating generalized expectation maximization (SAGE) algorithm. SAGE algorithm is a powerful tool for estimating channel parameters like ...
    • Particle swarm optimization of dipole arrays for superior MIMO capacity 

      Olgun, U.; Tunc, C. A.; Aktas, D.; Ertürk, V. B.; Altintas, A. (WILEY, 2009)
      The particle swarm optimization (PSO) technique is employed to design MIMO arrays for superior capacity. A channel model based on the method of moments solution of the electric field integral equation is utilized with PSO ...
    • Piecewise constant line fitting on noisy ramped signals by particle swarm optimization 

      Özer, Berk; Altıntaş, Ayhan; Moral, Gökhan; Arıkan, Orhan (IEEE, 2012)
      In this study, Particle Swarm Optimization(PSO) is proposed for change point (edge) detection on noisy ramped signals. By taking moving averages between detected edges, noise on ramped signals is filtered and desired ...
    • Real time noise-cancellation using ICA, PSO and PE 

      Bor, R. İrem; Ider, Y. Ziya; Arıkan, Orhan; Ertan, Erdem (IEEE, 2012)
      In order to provide noiseless transmission of speech in wireless communication systems a real-time implementable noise cancellation algorithm is developed. Speech and noise sources are not known but only their mixtures are ...
    • Signal denoising by piecewise continuous polynomial fitting 

      Yıldız, Aykut; Arıkan, Orhan (IEEE, 2010)
      Piecewise smooth signal denoising is cast as a non-linear optimization problem in terms of transition boundaries and a parametric smooth signal family. Optimal transition boundaries for a given number of transitions are ...
    • Successive cancelation approach for doppler frequency estimation in pulse doppler radar systems 

      Soğancı, Hamza; Gezici, Sinan (IEEE, 2010)
      In this paper, a successive cancelation approach is proposed to estimate Doppler frequencies of targets in pulse Doppler radar systems. This technique utilizes the Doppler domain waveform structure of the received signal ...
    • Unsupervised classification of remotely sensed images using Gaussian mixture models and particle swarm optimization 

      Arı, Çağlar; Aksoy, Selim (IEEE, 2010)
      Gaussian mixture models (GMM) are widely used for un-supervised classification applications in remote sensing. Expectation-Maximization (EM) is the standard algorithm employed to estimate the parameters of these models. ...