Results 41 to 50 of about 2,451 (213)
Sequence learning in a spiking neuronal network with memristive synapses
Neuromorphic Computing and Engineering, 2023 Brain-inspired computing proposes a set of algorithmic principles that hold promise for advancing artificial intelligence. They endow systems with self learning capabilities, efficient energy usage, and high storage capacity.
Younes Bouhadjar +5 more
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Monolithically Integrated SRAM-ReRAM Cache-Main Memory System [PDF]
, 2021 Emerging non-volatile memories are dense and potentially compatible with standard CMOS processes, enabling a monolithically integrated CPU-main memory chip.
Walden, Candace
core +1 more source
Optimal Design of FPGA Switch Matrix with Ion Mobility Based Nonvolatile ReRAM
Discrete Dynamics in Nature and Society, 2015 There are high demands for research of new device with greater accessing speed and stability to replace the current SRAM storage cell. The resistive random access memory (ReRAM) is a metal oxide which is based on nonvolatile memory device possessing the ...
Peng Hai-yun, Zhou Wen-gang
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Resistive Random Access Memory (ReRAM)
, 2019 Resistive Random-Access Memory (ReRAM) technology has been viewed as one of the most reliable non-volatile memories that have are emerging in markets. In this research paper, the revolution of ReRAM will be analyzed.
Dayalan, Muthu
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A compact Verilog-A ReRAM switching model
CoRR, 2017 The translation of emerging application concepts that exploit Resistive Random Access Memory (ReRAM) into large-scale practical systems requires realistic, yet computationally efficient, empirical models that can capture all observed physical devices.
Ioannis Messaris +4 more
openaire +2 more sources
An efficient read approach for memristive crossbar array
Memories - Materials, Devices, Circuits and Systems, 2023 Resistive random access memories (ReRAM) have drawn attention of researchers due to their unique properties with applications in in-memory computing, which allows storage and computation in the same unit.
Pravanjan Samanta +3 more
doaj +1 more source
Advanced Functional Materials, EarlyView.This study demonstrates that memristors can replace conventional 2T–1C driving circuits with simplified 1T–1 m architectures by exploiting resistance switching. With ultra‐low switching voltages (< ±0.2 V) and multi‐level resistance states, the memristors precisely control the current injected into organic light‐emitting diodes (OLEDs).
Dong Hyun Kim +6 more
wiley +1 more source
Multi-ReRAM synapses for artificial neural network training
, 2019 Metal-oxide-based resistive memory devices (ReRAM) are being actively researched as synaptic elements of neuromorphic co-processors for training deep neural networks (DNNs). However, device-level non-idealities are posing significant challenges.
Piveteau, Christophe +21 more
core +2 more sources
Effect of Programming Schemes on Short-Term Instability in 1T1R Configuration
IEEE AccessShort-term instability is one of the key challenges for redox-based resistive random-access memory (ReRAM) reaching practical applications in the field of neuromorphic computing.
Xiaohua Liu +7 more
doaj +1 more source
Stochastic resonance exploration in current-driven ReRAM devices [PDF]
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Vourkas, Ioannis +3 more
core +1 more source