摘要翻译：
随机数生成器(RNG)的各种构造技术所提供的密码安全性是当今发展的研究领域之一。在各种类型的RNG中，真随机比特发生器(TRBG)可以被认为是最不可预测和最安全的，因为它的随机性种子是由混沌源产生的。本文提出了一种基于GST忆阻器双涡卷吸引子电路的TRBG模型设计。利用GST忆阻器仿真器对混沌电路进行了实现和仿真，得到了输出电压和电感电流的混沌行为。此外，它们对输入电压的依赖表现出接近双涡旋的形式。通过接收输出电压的快速傅立叶变换(FFT)和Lyapunov指数来测试电路产生的随机性。
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英文标题：
《Implementation of True Random Number Generator based on Double-Scroll
  Attractor circuit with GST memristor emulator》
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作者：
Togzhan Abzhanova, Irina Dolzhikova, Alex Pappachen James
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最新提交年份：
2018
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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一级分类：Computer Science        计算机科学
二级分类：Emerging Technologies        新兴技术
分类描述：Covers approaches to information processing (computing, communication, sensing) and bio-chemical analysis based on alternatives to silicon CMOS-based technologies, such as nanoscale electronic, photonic, spin-based, superconducting, mechanical, bio-chemical and quantum technologies (this list is not exclusive). Topics of interest include (1) building blocks for emerging technologies, their scalability and adoption in larger systems, including integration with traditional technologies, (2) modeling, design and optimization of novel devices and systems, (3) models of computation, algorithm design and programming for emerging technologies.
涵盖基于硅CMOS技术替代品的信息处理（计算、通信、传感）和生物化学分析方法，如纳米级电子、光子、自旋、超导、机械、生物化学和量子技术（此列表不是唯一的）。感兴趣的主题包括：（1）新兴技术的构建块、其可伸缩性和在大型系统中的采用，包括与传统技术的集成；（2）新型设备和系统的建模、设计和优化；（3）新兴技术的计算模型、算法设计和编程。
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英文摘要：
  The cryptographic security provided by various techniques of random number generator (RNG) construction is one of the developing researches areas today. Among various types of RNG, the true random bit generator (TRBG) can be considered as the most unpredictable and most secured because its randomness seed is generated from chaotic sources. This paper proposes a design of TRBG model based on double-scroll attractors circuits with GST memristor. After implementation and simulation of the chaotic circuit with GST memristor emulator, the chaotic behavior of the output voltage and inductor current were received. Moreover, their dependence on the input voltage revealed the close to double-scroll form. The randomness generated from the proposed circuit was tested by receiving Fast Fourier Transform (FFT) and Lyapunov exponents of the output voltage.
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PDF链接：
https://arxiv.org/pdf/1805.06622