We evaluate the impact of temperature on the output behavior of a carbon nanotube field effect transistor （CNFET） based chaotic generator. The sources cause the variations in both current-voltage characteristics of ...We evaluate the impact of temperature on the output behavior of a carbon nanotube field effect transistor （CNFET） based chaotic generator. The sources cause the variations in both current-voltage characteristics of the CNFET device and an overall chaotic circuit is pointed out. To verify the effect of temperature variation on the output dynamics of the chaotic circuit, a simulation is performed by employing the CNFET compact model of Wong et al. in HSPICE with a temperature range from -100℃ to 100℃. The obtained results with time series, frequency spectra, and bifurcation diagram from the simulation demonstrate that temperature plays a significant role in the output dynamics of the CNFET-based chaotic circuit. Thus, temperature-related issues should be taken into account while designing a high-quality chaotic generator with high stability.展开更多
近年来,图像信息的传输安全性已经成为互联网领域的重要研究方向.本文提出了一种基于量子长短期记忆(quantum long-short term memory,QLSTM)网络的量子图像混沌加密方案.结果发现,因为QLSTM网络具有复杂的结构和较多的参数,应用QLSTM...近年来,图像信息的传输安全性已经成为互联网领域的重要研究方向.本文提出了一种基于量子长短期记忆(quantum long-short term memory,QLSTM)网络的量子图像混沌加密方案.结果发现,因为QLSTM网络具有复杂的结构和较多的参数,应用QLSTM网络对Lorenz混沌序列进行改进,其最大Lyapunov指数比原序列提高2.5465%,比经典长短期记忆(long-short term memory,LSTM)网络改进的序列提高0.2844%,同时在0—1测试中结果更接近1且更稳定,因此QLSTM网络改进的序列具备更优异的混沌性能,更难以被预测,提高了单一混沌系统加密的安全性.运用NCQI(novel quantum representation of color digital images)量子图像表示模型,将原始图像存储为量子态形式,利用QLSTM网络改进的序列分别控制三级径向扩散、量子广义Arnold变换和量子W变换,改变量子图像的灰度值与像素位置,生成最终的加密图像.本文提出的加密方案在统计学特性测试中,实现了RGB三通道平均信息熵均大于7.999,像素数改变率的平均值达99.6047%,统一平均变化强度的平均值为33.4613%,平均相关性为0.0038等,比其他一些传统方法具有更高的安全性,能够抵抗常见的攻击方式.展开更多
Abstract This paper proposes an image encryption algorithm LQBPNN(logistic quantum and back propagation neural network)based on chaotic sequences incorporating quantum keys.Firstly,the improved one-dimensional logisti...Abstract This paper proposes an image encryption algorithm LQBPNN(logistic quantum and back propagation neural network)based on chaotic sequences incorporating quantum keys.Firstly,the improved one-dimensional logistic chaotic sequence is used as the basic key sequence.After the quantum key is introduced,the quantum key is incorporated into the chaotic sequence by nonlinear operation.Then the pixel confused process is completed by the neural network.Finally,two sets of different mixed secret key sequences are used to perform two rounds of diffusion encryption on the confusing image.The experimental results show that the randomness and uniformity of the key sequence are effectively enhanced.The algorithm has a secret key space greater than 2182.The adjacent pixel correlation of the encrypted image is close to 0,and the information entropy is close to 8.The ciphertext image can resist several common attacks such as typical attacks,statistical analysis attacks and differential attacks.展开更多
Previous studies show that, in quantum chaotic and integrable systems, the so-called out-of-time-ordered correlator(OTOC) generically behaves differently at long times, while, it may show similar early growth in one-b...Previous studies show that, in quantum chaotic and integrable systems, the so-called out-of-time-ordered correlator(OTOC) generically behaves differently at long times, while, it may show similar early growth in one-body systems. In this paper, by means of numerical simulations, it is shown that OTOC has similar early growth in two quantum many-body systems, one integrable and one chaotic.展开更多
基金Supported by the Basic Science Research Program through the National Research Foundation of Korea Funded by the Ministry of Education,Science and Technology under Grant No 2012-0002777
文摘We evaluate the impact of temperature on the output behavior of a carbon nanotube field effect transistor （CNFET） based chaotic generator. The sources cause the variations in both current-voltage characteristics of the CNFET device and an overall chaotic circuit is pointed out. To verify the effect of temperature variation on the output dynamics of the chaotic circuit, a simulation is performed by employing the CNFET compact model of Wong et al. in HSPICE with a temperature range from -100℃ to 100℃. The obtained results with time series, frequency spectra, and bifurcation diagram from the simulation demonstrate that temperature plays a significant role in the output dynamics of the CNFET-based chaotic circuit. Thus, temperature-related issues should be taken into account while designing a high-quality chaotic generator with high stability.
文摘近年来,图像信息的传输安全性已经成为互联网领域的重要研究方向.本文提出了一种基于量子长短期记忆(quantum long-short term memory,QLSTM)网络的量子图像混沌加密方案.结果发现,因为QLSTM网络具有复杂的结构和较多的参数,应用QLSTM网络对Lorenz混沌序列进行改进,其最大Lyapunov指数比原序列提高2.5465%,比经典长短期记忆(long-short term memory,LSTM)网络改进的序列提高0.2844%,同时在0—1测试中结果更接近1且更稳定,因此QLSTM网络改进的序列具备更优异的混沌性能,更难以被预测,提高了单一混沌系统加密的安全性.运用NCQI(novel quantum representation of color digital images)量子图像表示模型,将原始图像存储为量子态形式,利用QLSTM网络改进的序列分别控制三级径向扩散、量子广义Arnold变换和量子W变换,改变量子图像的灰度值与像素位置,生成最终的加密图像.本文提出的加密方案在统计学特性测试中,实现了RGB三通道平均信息熵均大于7.999,像素数改变率的平均值达99.6047%,统一平均变化强度的平均值为33.4613%,平均相关性为0.0038等,比其他一些传统方法具有更高的安全性,能够抵抗常见的攻击方式.
基金supported by National Natural Science Foundation of China (No. 61402012)Doctor Foundation of Anhui University of Science and Technology
文摘Abstract This paper proposes an image encryption algorithm LQBPNN(logistic quantum and back propagation neural network)based on chaotic sequences incorporating quantum keys.Firstly,the improved one-dimensional logistic chaotic sequence is used as the basic key sequence.After the quantum key is introduced,the quantum key is incorporated into the chaotic sequence by nonlinear operation.Then the pixel confused process is completed by the neural network.Finally,two sets of different mixed secret key sequences are used to perform two rounds of diffusion encryption on the confusing image.The experimental results show that the randomness and uniformity of the key sequence are effectively enhanced.The algorithm has a secret key space greater than 2182.The adjacent pixel correlation of the encrypted image is close to 0,and the information entropy is close to 8.The ciphertext image can resist several common attacks such as typical attacks,statistical analysis attacks and differential attacks.
基金Supported by the National Natural Science Foundation of China under Grant Nos.11535011 and 11775210
文摘Previous studies show that, in quantum chaotic and integrable systems, the so-called out-of-time-ordered correlator(OTOC) generically behaves differently at long times, while, it may show similar early growth in one-body systems. In this paper, by means of numerical simulations, it is shown that OTOC has similar early growth in two quantum many-body systems, one integrable and one chaotic.
