12 citations · 53 across the 12 of their papers we have counts for
5 papers · 1 filter
Hybrid Synaptic Structure for Spiking Neural Network Realization
Sasan Razmkhah, Mustafa Altay Karamuftuoglu, Ali Bozbey
Neural networks and neuromorphic computing play pivotal roles in deep learning and machine vision. Due to their dissipative nature and inherent limitations, traditional semiconduct…
Superconductor Logic Implementation with All-JJ Inductor-Free Cell Library
Haolin Cong, Sasan Razmkhah, Mustafa Altay Karamuftuoglu +1
Single flux quantum (SFQ) technology has garnered significant attention due to its low switching power and high operational speed. Researchers have been actively pursuing more adva…
Design of a Superconducting Multiflux Non-Destructive Readout Memory Unit
Beyza Zeynep Ucpinar, Yasemin Kopur, Mustafa Altay Karamuftuoglu +2
Due to low power consumption and high-speed performance, superconductor circuit technology has emerged as an attractive and compelling post-CMOS technology candidate. However, the…
An On-Chip Trainable Neuron Circuit for SFQ-Based Spiking Neural Networks
Beyza Zeynep Ucpinar, Mustafa Altay Karamuftuoglu, Sasan Razmkhah +1
We present an on-chip trainable neuron circuit. Our proposed circuit suits bio-inspired spike-based time-dependent data computation for training spiking neural networks (SNN). The…
Unsupervised SFQ-Based Spiking Neural Network
Mustafa Altay Karamuftuoglu, Beyza Zeynep Ucpinar, Sasan Razmkhah +2
Single Flux Quantum (SFQ) technology represents a groundbreaking advancement in computational efficiency and ultra-high-speed neuromorphic processing. The key features of SFQ techn…