Results 211 to 220 of about 16,611 (244)
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RRAM based learning acceleration
Proceedings of the International Conference on Compilers, Architectures and Synthesis for Embedded Systems, 2016Deep Learning (DL) is becoming popular in a wide range of domains. Many emerging applications, ranging from image and speech recognition to natural language processing and information retrieval, rely heavily on deep learning techniques, especially the Neural Networks (NNs).
Yu Wang +5 more
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RRAM – Based - Equivalent Neural Network
2021The paper shows the capabilities of RRAM to model Neural Networks. The objectives of the work are to provide a likely RRAM based neuron model, and to emulate RRAM Bridge; which is used for synaptic weight adjustment. In order to analyze and design RRAM circuits, a Laplace domain expression has been derived. These equations can then be used for modeling
Ali Mohamed, Ali AbuAssal, Osama Rayis
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2016
In the age of Big Data, it has been always a dream for researchers to find the next generation nonvolatile memory with higher density, lower latency and lower cost. As a matter of fact, the last mainstream memory, NAND Flash memory, was created decades ago.
Huaqiang Wu +4 more
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In the age of Big Data, it has been always a dream for researchers to find the next generation nonvolatile memory with higher density, lower latency and lower cost. As a matter of fact, the last mainstream memory, NAND Flash memory, was created decades ago.
Huaqiang Wu +4 more
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Towards Automotive Grade Embedded RRAM
2018 48th European Solid-State Device Research Conference (ESSDERC), 2018Most types of resistive RAM (RRAM) explored over the past 20 years have suffered from reliability problems. As a result, RRAM has received relatively little consideration for use in automotive applications. The present article describes an improved subquantum Conductive Bridging RAM (CBRAM®) cell whose reliability appears robust enough for automotive ...
J.R. Jameson +12 more
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Unveiling switching mechanisms in RRAMs
2010 IEEE International Conference of Electron Devices and Solid-State Circuits (EDSSC), 2010Resistive random access memories (RRAMs) are deemed as one type of a few promising alternative non-volatile memories (NVMs) to the mainstreamNAND/NOR flash. The switching mechanisms for RRAMs, however, remain murky and a quantitative or semi-empiricalmodel is urgently needed.
null Zhiping Yu, null Yan Wang
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Bilayer Dielectrics for RRAM Devices
ECS Meeting Abstracts, 2018Non-volatile resistive random-access memory (RRAM) devices are currently being investigated as a low power, high density and high-speed alternative DRAM (1). A transition metal oxide dielectric layer is typically used as an insulating layer in a metal-insulator-metal (MIM) structure.
Durgamadhab Misra +8 more
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Volatility Characterization for RRAM Devices
IEEE Electron Device Letters, 2017Emerging technologies, such as resistive random access memory (RRAM), are being actively researched for its potential applications in developing new technologies inspired by brainlike neuromorphic computing. However, developing automated characterization algorithms for the metastable resistive state (RS) transitions, i.e., volatility in the myriad RRAM
Isha Gupta +4 more
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Vanadium Oxide Based RRAM Device
MRS Advances, 2017Forming-free bipolar resistive switching characteristics in a Vanadium oxide based sandwich structure is observed for the first time. The bottom conducting layer is the common ground electrode for all devices. The top conducting layer acts as an active element with an additional Cr/Al/Cr electrode patterned on its top for making contact. Different from
Zhenni Wan +2 more
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Microscopic KMC Modeling of Oxide RRAMs
2019We investigate the microscopic behavior of oxide-based resistive random-access memory (RRAM) cells by using a unique three-dimensional (3D) physical simulator. RRAMs are attracting substantial attention and are considered as the next generation of non-volatile memory technologies.
Toufik Sadi, Asen Asenov
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Memristor-based RRAM with applications
Science China Information Sciences, 2012Recently acclaimed the fourth fundamental circuit element, the memristor was theoretically predicted by Leon Chua in 1971, although its single device electronic implementation eluded the attention of integrated circuit designers for the past three decades and was first reported in 2008 by the Hewlett-Packard (HP) Laboratory researchers while developing
ShuKai Duan +4 more
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