Odaklanan Nöron

Ilker Cam*, F. Boray Tek

*Bu çalışma için yazışmadan sorumlu yazar

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde BölümKonferans katkısıbilirkişi

1 Atıf (Scopus)

Özet

The traditional neural network topology is not flexible to change during the training process. Every neuron and it's independent weights in the network are part of the solution function. The proposed focusing neuron model utilizes inter-dependent weights produced by a focusing function. This neuron can change it's focus position and aperture. This property allows a flexible-dynamic network topology, which can be trained using conventional back-propagation algorithm. Our experiments show that focusing neuron neural networks achieve higher success than fully connected neural networks.

Tercüme edilen katkı başlığıFocusing neuron
Orijinal dilTürkçe
Ana bilgisayar yayını başlığı2017 25th Signal Processing and Communications Applications Conference, SIU 2017
YayınlayanInstitute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)9781509064946
DOI'lar
Yayın durumuYayınlandı - 27 Haz 2017
Harici olarak yayınlandıEvet
Etkinlik25th Signal Processing and Communications Applications Conference, SIU 2017 - Antalya, Turkey
Süre: 15 May 201718 May 2017

Yayın serisi

Adı2017 25th Signal Processing and Communications Applications Conference, SIU 2017

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???event.eventtypes.event.conference???25th Signal Processing and Communications Applications Conference, SIU 2017
Ülke/BölgeTurkey
ŞehirAntalya
Periyot15/05/1718/05/17

Bibliyografik not

Publisher Copyright:
© 2017 IEEE.

Keywords

  • artificial neural network
  • focusing neuron

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