一种改进的金属氧化物忆阻器模型

2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST) Pub Date : 2022-06-08 DOI:10.1109/mocast54814.2022.9837519

V. Mladenov, S. Kirilov

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引用次数: 2

摘要

忆阻器是一种新型的、有发展前途的电子存储元件，有可能取代现有的CMOS元件。由于其纳米尺寸、低能耗和记忆效应，可用于神经网络、记忆横条、可重构模拟和数字器件等电子方案。本文提出了一种简单、快速的修正金属氧化物忆阻器模型。生成了相应的LTSPICE库模型，并在一个简单的神经网络中成功地进行了分析。模型的行为符合忆阻器元件的基本指纹。建立了该方法在忆阻器器件中的适用性。

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A Modified Metal Oxide Memristor Model

The memristor is a new and promising electronic memory element and could be a possible replacement for the present CMOS components. Due to its nano size, low energy usage and memory effect, it could be used in neural nets, memory crossbars, reconfigurable analogue and digital devices and other electronic schemes. In this paper, a simple, fast functioning modified metal oxide memristor model is suggested. Its corresponding LTSPICE library model is generated and successfully analyzed in a simple neural network. The model’s behavior is in accordance with the basic fingerprints of the memristor elements. Its proper operation and applicability in memristor-based devices is established.

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2022 11th International Conference on Modern Circuits and Systems Technologies (MOCAST)

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