Now showing items 1-10 of 10

    • Adaptive filtering approaches for non-Gaussian stable processes 

      Arıkan, O.; Belge, M.; Çetin, A. E.; Erzin, E. (Institute of Electrical and Electronics Engineers, 1995)
      A large class of physical phenomenon observed in practice exhibit non-Gaussian behavior. In this paper, α-stable distributions, which have heavier tails than Gaussian distribution, are considered to model non-Gaussian ...
    • Average fisher information optimization for quantized measurements using additive independent noise 

      Balkan, Gokce Osman; Gezici, Sinan (IEEE, 2010)
      Adding noise to nonlinear systems can enhance their performance. Additive noise benefits are observed also in parameter estimation problems based on quantized observations. In this study, the purpose is to find the optimal ...
    • Bounds on the capacity of random insertion and deletion-additive noise channels 

      Rahmati, M.; Duman, T. M. (IEEE, 2013)
      We develop several analytical lower bounds on the capacity of binary insertion and deletion channels by considering independent uniformly distributed (i.u.d.) inputs and computing lower bounds on the mutual information ...
    • Noise enhanced detection in restricted Neyman-Pearson framework 

      Bayram, S.; Gültekin, San; Gezici, Sinan (IEEE, 2012-06)
      Noise enhanced detection is studied for binary composite hypothesis-testing problems in the presence of prior information uncertainty. The restricted Neyman-Pearson (NP) framework is considered, and a formulation is obtained ...
    • Noise enhanced detection in the restricted Bayesian framework 

      Bayram, Suat; Gezici, Sinan; Poor H.V. (IEEE, 2010)
      Effects of additive independent noise are investigated for sub-optimal detectors according to the restricted Bayes criterion. The statistics of optimal additive noise are characterized. Also, sufficient conditions for ...
    • On the optimality of stochastic signaling under an average power constraint 

      Goken, C.; Gezici, S.; Arikan, O. (2010)
      In this paper, stochastic signaling is studied for scalar valued binary communications systems over additive noise channels in the presence of an average power constraint. For a given decision rule at the receiver, the ...
    • Robust least squares methods under bounded data uncertainties 

      Vanli, N. D.; Donmez, M. A.; Kozat, S. S. (Academic Press, 2015)
      We study the problem of estimating an unknown deterministic signal that is observed through an unknown deterministic data matrix under additive noise. In particular, we present a minimax optimization framework to the least ...
    • Sparsity order estimation for single snapshot compressed sensing 

      Romer F.; Lavrenko, A.; Del Galdo G.; Hotz, T.; Arikan, O.; Thoma, R.S. (IEEE Computer Society, 2015)
      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 ...
    • Stochastic resonance in binary composite hypothesis-testing problems in the Neyman-Pearson framework 

      Bayram, S.; Gezici, S. (Elsevier, 2012-02-20)
      Performance of some suboptimal detectors can be enhanced by adding independent noise to their inputs via the stochastic resonance (SR) effect. In this paper, the effects of SR are studied for binary composite hypothesis-testing ...
    • Stochastic signaling under second and fourth moment constraints 

      Göken, Çağrı; Gezici, Sinan; Arıkan, Orhan (IEEE, 2010)
      Stochastic signaling is investigated under second and fourth moment constraints for the detection of scalar-valued binary signals in additive noise channels. Sufficient conditions are derived to determine when the use of ...