Results 81 to 90 of about 2,956 (211)
Small, EarlyView.Bio‐inspired computing offers a route to highly energy‐efficient artificial intelligence. The unique physical properties of two‐dimensional (2D) materials can further enhance such computing approaches. This perspective highlights recent developments in 2D materials‐based neuromorphic devices and discusses future opportunities for integrating such novel
Jin Feng Leong +9 more
wiley +1 more source
Small, EarlyView.BNNT rods incorporated into MWCNT–ZnO quantum dot networks regulate charge transport and suppress leakage in flexible, transparent resistive memory devices. The resulting hybrid architecture preserves nonvolatile switching under static bending and after low‐temperature exposure and subcutaneous implantation.
Jaeho Shim +11 more
wiley +1 more source
Design Framework for ReRAM-Based DNN Accelerators with Accuracy and Hardware Evaluation
, 2022 To achieve faster design closure, there is a need to provide a design framework for the design of ReRAM-based DNN (deep neural network) accelerator at the early design stage.
Wei-Kai Cheng +2 more
core +1 more source
Small, EarlyView.Real‐world graph data are directly mapped onto an mCBA, enabling node similarity to be computed through a single current readout. Strongly nonlinear devices suppress long‐range multi‐hop contributions while preserving local connectivity, whereas weakly nonlinear devices allow excessive signal propagation.
Jae‐Hyun Lee +7 more
wiley +1 more source
, 2018 The stochastic neuron is a key for event-based probabilistic neural networks. We propose a stochastic neuron using a metal-oxide resistive random-Access memory (ReRAM).
Yuan, Jiann Shiun, Lin, Jie
core +1 more source
Noise and Drift Models for Protonic ECRAM and Their Impact on Analog In‐Memory Computing
Advanced Computing, Volume 1, Issue 1, December 2026.Read noise and conductance drift of protonic electrochemical random‐access memory (ECRAM) are characterized and described using physics‐informed device models. These models connect proton transport and measured current fluctuations to analog in‐memory computing (AIMC) performance.
Xin Su, Haoran Liu, Qing Cao, Ning Li
wiley +1 more source
Low‐Frequency Noise Evolution in Thin SiNx ReRAMs After Sequential Constant Voltage Stress
physica status solidi (a), Volume 223, Issue 21, 11 November 2026.In this work, thin SiNx films in MIS ReRAM cells are stressed with a constant voltage for various sequential durations (25, 45, 65, 110 and 250 s) and the low‐frequency noise signal generated after each stress duration is measured using different sampling rates.
Alexandros E. Mavropoulis +7 more
wiley +1 more source
A thermal-aware optimization framework for ReRAM-based deep neural network acceleration
, 2020 Resistive RAM (ReRAM) is widely regarded as a promising platform for deep neural network (DNN) acceleration. However, the ReRAM device suffers from severe thermal problems that degrade the lifetime and inference accuracy of the ReRAM-based DNN ...
Myeonggu Kang +5 more
core +1 more source
Triple‐Level Content‐Addressable Vertical NAND Flash Memory
Advanced Science, Volume 13, Issue 61, 3 November 2026.Commercial triple‐level‐cell V‐NAND flash memory is transformed into a compact content‐addressable memory by directly exploiting its eight threshold‐voltage states. A parity‐split search scheme preserves storage density while enabling reliable multi‐level and don't‐care matching. Parallel word‐line search delivers up to 24‐fold higher throughput and 54.
Sung‐Ho Park +8 more
wiley +1 more source
Advanced Electronic MaterialsResistive Random Access Memory (ReRAM) devices offer a promising solution for next‐generation non‐volatile memory and neuromorphic computing systems. Yet, existing compact models fail to capture analog resistive switching behavior of ReRAM devices.
Matteo Galetta +9 more
doaj +1 more source