Learning and Spatiotemporally Correlated Functions Mimicked in Oxide-Based Artificial Synaptic Transistors

التفاصيل البيبلوغرافية
العنوان: Learning and Spatiotemporally Correlated Functions Mimicked in Oxide-Based Artificial Synaptic Transistors
المؤلفون: Wan, Chang Jin, Zhu, Li Qiang, Shi, Yi, Wan, Qing
سنة النشر: 2013
المجموعة: Computer Science
Condensed Matter
مصطلحات موضوعية: Condensed Matter - Materials Science, Computer Science - Emerging Technologies
الوصف: Learning and logic are fundamental brain functions that make the individual to adapt to the environment, and such functions are established in human brain by modulating ionic fluxes in synapses. Nanoscale ionic/electronic devices with inherent synaptic functions are considered to be essential building blocks for artificial neural networks. Here, Multi-terminal IZO-based artificial synaptic transistors gated by fast proton-conducting phosphosilicate electrolytes are fabricated on glass substrates. Proton in the SiO2 electrolyte and IZO channel conductance are regarded as the neurotransmitter and synaptic weight, respectively. Spike-timing dependent plasticity, short-term memory and long-term memory were successfully mimicked in such protonic/electronic hybrid artificial synapses. And most importantly, spatiotemporally correlated logic functions are also mimicked in a simple artificial neural network without any intentional hard-wire connections due to the naturally proton-related coupling effect. The oxide-based protonic/electronic hybrid artificial synaptic transistors reported here are potential building blocks for artificial neural networks.
نوع الوثيقة: Working Paper
URL الوصول: http://arxiv.org/abs/1304.7072
رقم الأكسشن: edsarx.1304.7072
قاعدة البيانات: arXiv