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首页> 外文期刊>Proceedings of the IEEE >Analysis of Passive Memristive Devices Array: Data-Dependent Statistical Model and Self-Adaptable Sense Resistance for RRAMs
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Analysis of Passive Memristive Devices Array: Data-Dependent Statistical Model and Self-Adaptable Sense Resistance for RRAMs

机译:无源忆阻器件阵列分析:RRAM的数据相关统计模型和自适应感应电阻

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摘要

In this paper, a 2 × 2 equivalent statistical circuit model is presented to deal with sneak currents and random data distributions for design and analysis of n x m passive memory arrays of memristive devices. This data-dependent 2 × 2 model enables a broad range of analysis, such as the optimum detection voltage margin, with computational efficiency and no limit on the memory array size. We propose self-adaptable sense resistors that can find their statistical optimum values for reading stored data patterns by composing them with either a replica of a part of resistive random access memory (RRAM) array or a part of RRAM array itself. Self-adaptable resistors can increase the average voltage detection margin by 46%, and reduce the average current consumption by 14% for the case of a 128 × 128 passive array with OFF-to-ON resistance ratio of 103.
机译:本文提出了一个2×2等效统计电路模型来处理潜电流和随机数据分布,以设计和分析n x m忆阻器件的无源存储阵列。这种依赖于数据的2×2模型可以进行广泛的分析,例如最佳检测电压裕度,计算效率高,并且对存储阵列的大小没有限制。我们提出了一种自适应电阻,可以通过将其与电阻随机存取存储器(RRAM)阵列的一部分或RRAM阵列本身的一部分组成副本,找到用于读取存储数据模式的统计最优值。自适应电阻可以将平均电压检测裕度提高46%,对于128×128无源阵列的导通电阻比为10 3

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