Now showing items 1-10 of 10

    • Adaptive and efficient nonlinear channel equalization for underwater acoustic communication 

      Kari, D.; Vanli, N. D.; Kozat, S. S. (Elsevier B.V., 2017)
      We investigate underwater acoustic (UWA) channel equalization and introduce hierarchical and adaptive nonlinear (piecewise linear) channel equalization algorithms that are highly efficient and provide significantly improved ...
    • Boosted LMS-Based Piecewise Linear Adaptive Filters 

      Kari, D.; Marivani, I.; Delibalta, I.; Kozat, S.S. (European Signal Processing Conference, EUSIPCO, 2016)
      We introduce the boosting notion extensively used in different machine learning applications to adaptive signal processing literature and implement several different adaptive filtering algorithms. In this framework, we ...
    • Competitive and online piecewise linear classification 

      Ozkan H.; Donmez, M.A.; Pelvan O.S.; Akman, A.; Kozat, S.S. (2013)
      In this paper, we study the binary classification problem in machine learning and introduce a novel classification algorithm based on the 'Context Tree Weighting Method'. The introduced algorithm incrementally learns a ...
    • Fast and accurate analysis of large-scale composite structures with the parallel multilevel fast multipole algorithm 

      Ergül, Ö.; Gürel, L. (Optical Society of America, 2013)
      Accurate electromagnetic modeling of complicated optical structures poses several challenges. Optical metamaterial and plasmonic structures are composed of multiple coexisting dielectric and/or conducting parts. Such ...
    • Linear MMSE-optimal turbo equalization using context trees 

      Kim, K.; Kalantarova, N.; Kozat, S. S.; Singer, A. C. (IEEE, 2013)
      Formulations of the turbo equalization approach to iterative equalization and decoding vary greatly when channel knowledge is either partially or completely unknown. Maximum aposteriori probability (MAP) and minimum ...
    • A new method for nonlinear circuit simulation in time domain: NOWE 

      Ocalı, O.; Tan, M. A.; Atalar, Abdullah (Institute of Electrical and Electronics Engineers, 1996-03)
      A new method for the time-domain solution of general nonlinear dynamic circuits is presented. In this method, the solutions of the state variables are computed by using their time derivatives up to some order at the initial ...
    • Piecewise nonlinear regression via decision adaptive trees 

      Vanli, N.D.; Sayin, M.O.; Ergüt, S.; Kozat, S.S. (European Signal Processing Conference, EUSIPCO, 2014)
      We investigate the problem of adaptive nonlinear regression and introduce tree based piecewise linear regression algorithms that are highly efficient and provide significantly improved performance with guaranteed upper ...
    • Quantitative comparison of rooftop and RWG basis functions 

      Gürel, L.; Şendur, I. K.; Sertel, K. (IEEE, Piscataway, NJ, United States, 1997)
      The `rooftops' (RT) basis functions (BFs) are well suited for the modeling of geometries that conform to Cartesian coordinates, whereas the Rao, Wilton, and Glisson subdomains (RWG) BFs are capable of modeling flat-faceted ...
    • Solution of radiation problems using the fast multipole method 

      Gürel, L.; Şendur, İ. K. (IEEE (Institute of Electrical and Electronics Engineers), 1997)
      Electromagnetic radiation problems involving electrically large radiators and reflectors are solved using the fast multipole method (FMM). The FMM enables the solution of large problems with existing computational resources ...
    • Utilization of the recursive shortest spanning tree algorithm for video-object segmentation by 2-D affine motion modeling 

      Tuncel, E.; Onural, L. (IEEE, 2000)
      A novel video-object segmentation algorithm is proposed, which takes the previously estimated 2-D dense motion vector field as input and uses the generalized recursive shortest spanning tree method to approximate each ...