Results 81 to 90 of about 16,611 (244)
Advanced Electronic Materials, 2022 Multifunctional nonvolatile photoelectronic memory devices with multilevel storage and logic operation are expected to perform logic‐in‐memory computing tasks and overcome the von Neumann bottleneck.
Jiacheng Li +5 more
doaj +1 more source
Multi-level, forming and filament free, bulk switching trilayer RRAM for neuromorphic computing at the edge. [PDF]
Nat CommunCMOS-RRAM integration holds great promise for low energy and high throughput neuromorphic computing. However, most RRAM technologies relying on filamentary switching suffer from variations and noise, leading to computational accuracy loss, increased ...
Park J +13 more
europepmc +2 more sources
Versatile stochastic dot product circuits based on nonvolatile memories for high performance neurocomputing and neurooptimization. [PDF]
, 2019 The key operation in stochastic neural networks, which have become the state-of-the-art approach for solving problems in machine learning, information theory, and statistics, is a stochastic dot-product.
Mahmoodi, MR, Prezioso, M, Strukov, DB
core +1 more source
Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference
Advanced Electronic Materials, EarlyView.This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho +6 more
wiley +1 more source
Nanoscale Research Letters, 2023 The modern-day computing technologies are continuously undergoing a rapid changing landscape; thus, the demands of new memory types are growing that will be fast, energy efficient and durable.
Furqan Zahoor +6 more
doaj +1 more source
Advanced Energy and Sustainability Research, EarlyView.Triboelectric nanogenerators are vital for sustainable energy in future technologies such as wearables, implants, AI, ML, sensors and medical systems. This review highlights improved TENG neuromorphic devices with higher energy output, better stability, reduced power demands, scalable designs and lower costs.
Ruthran Rameshkumar +2 more
wiley +1 more source
Dendritic-Inspired Processing Enables Bio-Plausible STDP in Compound Binary Synapses
, 2018 Brain-inspired learning mechanisms, e.g. spike timing dependent plasticity (STDP), enable agile and fast on-the-fly adaptation capability in a spiking neural network. When incorporating emerging nanoscale resistive non-volatile memory (NVM) devices, with
Saxena, Vishal, Wu, Xinyu
core +1 more source
Advanced Intelligent Discovery, EarlyView.Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj +2 more
wiley +1 more source
Advanced Intelligent Systems, EarlyView.This study investigates the neuromorphic plasticity behavior of 180 nm bulk complementary metal oxide semiconductor (CMOS) transistors at cryogenic temperatures. The observed hysteresis data reveal a signature of synaptic behavior in CMOS transistors at 4 K.
Fiheon Imroze +8 more
wiley +1 more source
Stretchable and Wearable Resistive Switching Random‐Access Memory
Advanced Intelligent Systems, 2020 In the era of big data, with the development and application of 5G technology, artificial intelligence technology, and wearable electronics, the acquisition, storage, search, sharing, analysis, and even visual presentation require huge amounts of data in
Qiuwei Shi +3 more
doaj +1 more source