Now showing items 1-4 of 4

    • A novel objective function minimization for sparse spatial filters 

      Onaran, İ.; İnce, N. F.; Çetin, A. Enis (IEEE, 2014)
      Common spatial pattern (CSP) method is widely used in brain machine interface (BMI) applications to extract features from the multichannel neural activity through a set of spatial projections. The CSP method easily overfits ...
    • A signal representation approach for discrimination between full and empty hazelnuts 

      Onaran, İbrahim; İnce, N. F.; Tevfik, A. H.; Çetin, A. Enis (IEEE, 2007)
      We apply a sparse signal representation approach to impact acoustic signals to discriminate between empty and full hazelnuts. The impact acoustic signals are recorded by dropping the hazelnut shells on a metal plate. The ...
    • Subset selection with structured dictionaries in classification 

      İnce, N. F.; Göksu, F.; Tewfik, A. H.; Onaran, İbrahim; Çetin, A. Enis (EURASIP, 2007)
      This paper describes a new approach for the selection of discriminant time-frequency features for classification. Unlike previous approaches that use the individual discrimination power of expansion coefficients, the ...
    • Wheat and hazelnut inspection with impact acoustics time-frequency patterns 

      İnce, N. F.; Onaran, İbrahim; Tewfik, A. H.; Kalkan, H.; Pearson, T.; Çetin, A. Enis; Yardimci, Y. (ASABE, 2007-06)
      Kernel damage caused by insects and fungi is one of the most common reason for poor flour quality. Cracked hazelnut shells are prone to infection by cancer producing mold. We propose a new adaptive time-frequency classification ...