Spiking Neural Network Applications
Küçük Resim Yok
Tarih
2017
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Ieee
Erişim Hakkı
info:eu-repo/semantics/closedAccess
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.
Açıklama
2017 International Artificial Intelligence and Data Processing Symposium (IDAP) -- SEP 16-17, 2017 -- Malatya, TURKEY
Anahtar Kelimeler
Artificial Neural Networks, Spiking Neural Network, Delay Time, Synapses, BackPropagation, Population Coding, Gaussian Receptive Fields
Kaynak
2017 International Artificial Intelligence and Data Processing Symposium (Idap)
WoS Q Değeri
N/A
Scopus Q Değeri
N/A
