Results 101 to 110 of about 5,289 (241)
Neuromorphic Denoising with Fully Analog Memristive In‐Memory Computing
Advanced Intelligent Systems, EarlyView.This article borrows the concepts of episodic memory in human brains to experimentally implement a memristor‐based neuromorphic denoising process. A homogeneous memristor processing unit is experimentally demonstrated for both temporal storage and neural network computation, imitating the synapses in the human brain.
Daijing Shi +5 more
wiley +1 more source
How significant is SET programming strategy in enhancing RRAM technology? [PDF]
International audienceThis paper benchmarks a range of programming strategies for resistive random-access memory (RRAM), employing both voltage-and current-mode methods in single pulse, and progressive verify formats.
Pillonnet, Gaël +2 more
core +1 more source
Exploiting Ferroelectric and Spintronic Dynamics for Neural Network Computation
Advanced Intelligent Systems, EarlyView.Ferroelectric and spintronic devices, relying on the control of polarization and magnetization, offer intrinsically fast, durable, energy‐efficient, and low‐latency building blocks for analog in‐memory computing. The hysteretic dynamics of an order parameter are leveraged to provide nonvolatile, multistate memory and nonlinear switching. Brain‐inspired
Dashiell Harrison +4 more
wiley +1 more source
Training-based forming process for RRAM yield improvement [PDF]
, 2014 [[abstract]]Over the past decade, the resistive memory device known as RRAM has been studied extensively in many ways, and many of its problems have been identified, discussed, and some solved.
H.-C. Shih;C.-Y. Chen;C.-W. Wu;C.-H. Lin;S.-S. Sheu
core +1 more source
Design and Application of Oxide-Based Resistive Switching Devices for Novel Computing Architectures
IEEE Journal of the Electron Devices Society, 2016 Resistive switching behaviors of oxide-based resistive random access memory (RRAM) and the applications for the data storage and computing systems have been widely studied.
Jinfeng Kang +8 more
doaj +1 more source
Interdisciplinary Materials, EarlyView.Neuromorphic hardware enables the integration of sensing, memory, and computing for intelligent artificial perception. Recent advances in multimodal fusion further highlight its potential for embodied intelligence and next‐generation human–machine interfaces.
Yixin Zhu +3 more
wiley +1 more source
CMOS friendly electrode material screening for HfOx-based RRAM [PDF]
, 2013 This project is aim to study the Resistive Radom-Access Memory (RRAM), which is expected to be the replacement of flash memory and a next generation memory.
Yan, Haiping
core
Distributed In-Memory Computing on Binary RRAM Crossbar [PDF]
, 2017 The recently emerging resistive random-access memory (RRAM) can provide nonvolatile memory storage but also intrinsic computing for matrix-vector multiplication, which is ideal for the low-power and high-throughput data analytics accelerator performed in
Hao Yu +9 more
core +1 more source
Conjugated Polymers Engineered for Flexible/Stretchable Electronics
Journal of Polymer Science, EarlyView.This review highlights glass transition temperature (Tg) as the central parameter linking molecular structure to device performance in conjugated polymers. By tuning backbone rigidity, side‐chain architecture, and dynamic bonding, Tg governs the balance between π–π stacking–enabled charge transport and mechanical compliance.
Yunchong Yang +5 more
wiley +1 more source
MXene‐Based Flexible Memory and Neuromorphic Devices
Small, EarlyView.The unique two‐dimensional structure, excellent electrical conductivity, and diverse surface groups of MXenes have garnered significant attention. Coupled with their exceptional flexibility, MXene‐based devices hold immense potential for flexible memory and neuromorphic systems. This review comprehensively discusses the fundamentals of flexible devices,
Yan Li +13 more
wiley +1 more source