Fast global fuzzy C-means clustering for ECG signal classification EKG i̇şaretlerini siniflamak için hizli global bulanik C-ortalama öbekleşme

KOÇYİĞİT Y., KILIÇ İ.

18th IEEE Signal Processing and Communications Applications Conference, SIU 2010, Diyarbakır, Türkiye, 22 - 24 Nisan 2010, ss.189-191, (Tam Metin Bildiri) identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Doi Numarası: 10.1109/siu.2010.5651537
  • Basıldığı Şehir: Diyarbakır
  • Basıldığı Ülke: Türkiye
  • Sayfa Sayıları: ss.189-191
  • Manisa Celal Bayar Üniversitesi Adresli: Evet

Özet

Fuzzy clustering plays an important role in solving problems in the areas of pattern recognition and fuzzy model identification. The Fuzzy C-Means algorithm is one of widely used algorithms. It is based on optimizing an objective function, being responsive to initial conditions; the algorithm usually leads to local minimum results. Aiming at above problem, the fast global Fuzzy C-Means clustering algorithm (FGFCM) has been proposed, which is an incremental approach to clustering, and does not depend on any initial conditions. The algorithm was applied on ECG signals to classification. ©2010 IEEE.