Nonlinear filtering design using dynamic neural networks with fast training

Becerikli Y.

COMPUTER AND INFORMATION SCIENCES - ISCIS 2003, cilt.2869, ss.601-610, 2003 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 2869
  • Basım Tarihi: 2003
  • Dergi Adı: COMPUTER AND INFORMATION SCIENCES - ISCIS 2003
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, EMBASE, MathSciNet, Philosopher's Index, zbMATH
  • Sayfa Sayıları: ss.601-610
  • Kocaeli Üniversitesi Adresli: Evet

Özet

This paper presents nonlinear filtering using dynamic neural networks (DNNs). In addition, the general usage of linear filtering structure is given. DNN which has a quasi-linear structure has been effectively used as a filter with fast training algorithm such as Levenberg-Marquardt method. The test results are shown that the performance of DNN as linear and nonlinear filters is satisfactory.