Yazar "Gül, Fatih" için listeleme
-
Design and optimisations of metal-oxide artificial synaptic device based machine learning model
Yılmaz, Yıldıran; Gül, Fatih (IEEE, 2024)Synaptic device-based neural network models are increasingly favored for their energy-efficient computing capabilities. However, as the demand for scalable and resource-efficient computing solutions continues to grow, there ... -
Effects of 5 G mobile phone network electromagnetic field exposure on testicular endoplasmic reticulum stress and the protective role of coenzyme Q10
Yılmaz, Hamit; Tümkaya, Levent; Mercantepe, Tolga; Yılmaz, Adnan; Gül, Fatih; Suzan, Zehra Topal (Elsevier, 2025)Aim. Nowadays, the electromagnetic field (EMF) has become an issue of electromagnetic pollution . This study aimed to determine the effect of 5 G Fr1 frequency band EMF waves on endoplasmic reticulum (ER) stress in testicular ... -
Electronically controllable fully floating memcapacitor circuit
Gür, Müslüm; Akar, Funda; Orman, Kamil; Babacan, Yunus; Yeşil, Abdullah; Gül, Fatih (Springer, 2023)Memcapacitor is a type of capacitor but exhibits nonlinear behavior, and its capacitance depends on the past capacitance value. Researchers focused on the memcapacitors and meminductors upon postulation of memristor which ... -
Harmonic problems in renewable and sustainable energy systems: A comprehensive review
Eroğlu, Hasan; Cüce, Erdem; Cüce, Pınar Mert; Gül, Fatih; İskenderoğlu, Abdulkadir (Elsevier, 2021)Harmonics are known as distortions in the form of voltage and current, which are driven by the nonlinear loads in the network. Harmonics can be basically asserted as the most common problem in renewable-based power generation ... -
Memristive synapses as building blocks of neuromorphic artificial intelligence (AI) hardware
Gül, Fatih (IEEE, 2024)The rapid advancement of artificial intelligence (AI) has significantly expanded the use of machine learning and deep learning, yet traditional Von-Neumann architecture-based computers struggle with the energy demands of ... -
Nano-scale single layer TiO2-based artificial synaptic device
Gül, Fatih (Springer Heidelberg, 2020)Synaptic nano-electronic devices for brain-inspired computing have become increasingly popular because of their biological neuron-like properties such as massive parallelism with lower power consumption. Metal oxide-based ... -
Neuro-inspired hardware solutions for high-performance computing: A TiO2-based nano-synaptic device approach with backpropagation
Yılmaz, Yıldıran; Gül, Fatih (Elsevier, 2024)Computer-based machine learning algorithms that produce impressive performance results are computationally demanding and thus subject to high energy consumption during training and testing. Therefore, compact neuro-inspired ... -
Optimizing memristor-based synaptic devices for enhanced energy efficiency and accuracy in neuromorphic machine learning
Gökgöz, Baki; Aydın, Tolga; Gül, Fatih (IEEE, 2024)The traditional Von Neumann computing architecture, which necessitates data transfer between external memory and the processor, incurs significant energy and time costs when running deep learning (DL) and machine learning ... -
A simplified method to determine carrier transport mechanisms of metal-oxide resistive random access memory (RRAM) devices
Gül, Fatih (Elsevier, 2021)The current carrier transport mechanism in non-linear resistance states of the current-voltage (I-V) curves of the resistance changing or resistive switching (RS) based random access memory (RRAM) devices would help to ...
