Spiking Neural Network Applications

Celik G., TALU M. F.

2017 International Artificial Intelligence and Data Processing Symposium (IDAP), Malatya, Türkiye, 16 - 17 Eylül 2017 identifier identifier

  • Yayın Türü: Bildiri / Tam Metin Bildiri
  • Cilt numarası:
  • Doi Numarası: 10.1109/idap.2017.8090266
  • Basıldığı Şehir: Malatya
  • Basıldığı Ülke: Türkiye
  • İnönü Üniversitesi Adresli: Evet

Özet

Spiking Neural Network (SNN) are 3rd Generation Artificial Neural Networks (ANN) models. The fact that time information is processed in the form of spikes and there are multiple synapses between cells (neurons) are the most important features that distinguish SNN from previous generations. In this study, artificial learning systems which can learn by using basic logical operators such as AND, OR, XOR have been developed in order to understand SNN structure. In SNN, we tried to find optimal values for these parameters by examining the effect of the number of connections between cells and delays between connections to learning success.