Sine Chaotification Model for Enhancing Chaos and Its Hardware Implementation
Sine Chaotification Model for Enhancing Chaos and Its Hardware Implementation
复制标题
增强混沌的正弦混沌模型及其硬件实现
DOI：
10.1109/tie.2018.2833049
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发表时间：
2019-02-01
影响因子：
7.7
通讯作者：
Zhou, Yicong
中科院分区：
文献类型：
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作者：
Hua, Zhongyun;Zhou, Binghang;Zhou, Yicong
当混沌系统用于不同的实际应用中，例如非线性控制和密码学时，强烈要求其复杂的混乱动态。但是，许多现有的混乱系统具有简单的复杂性，这给基于混乱的应用带来了负面影响。为了解决这个问题，本文引入了正弦混乱模型（SCM），作为一般框架，以增强现有一维（1-D）混乱图的混乱复杂性。 SCM使用正弦函数作为非线性混沌变换，并将其应用于1-D混沌图的输出。与种子图相比，SCM的混沌图增强的混乱图具有更好的混乱复杂性和更大的混沌范围。理论分析验证了SCM的效率。为了显示SCM的性能，我们将SCM应用于三个现有的混沌图，并分析获得的增强混沌图的动力学特性。绩效评估证明，与种子混沌图相比，这三个增强的混沌图具有复杂的动态行为。为了显示SCM的实现简单性，我们使用现场编程的门阵列实现了三个增强的混沌图。为了调查实际应用中的SCM，我们使用增强的混沌图设计了伪数量生成器。
When chaotic systems are used in different practical applications, such as nonlinear control and cryptography, their complex chaos dynamics are strongly required. However, many existing chaotic systems have simple complexity, and this brings negative effects to chaos-based applications. To address this issue, this paper introduces a sine chaotification model (SCM) as a general framework to enhance the chaos complexity of existing one-dimensional (1-D) chaotic maps. The SCM uses a sine function as a nonlinear chaotification transform and applies it to the output of a 1-D chaotic map. The resulting enhanced chaotic map of the SCM has better chaos complexity and a much larger chaotic range than the seed map. Theoretical analysis verifies the efficiency of the SCM. To show the performance of the SCM, we apply SCM to three existing chaotic maps and analyze the dynamics properties of the obtained enhanced chaotic maps. Performance evaluations prove that the three enhanced chaotic maps have more complicated dynamics behaviors than their seed chaotic maps. To show the implementation simplicity of the SCM, we implement the three enhanced chaotic maps using the field-programmable gate array. To investigate the SCM in practical application, we design pseudorandom number generators using the enhanced chaotic maps.