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相关概念视频

Linear time-invariant Systems01:23

Linear time-invariant Systems

262
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
262
Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

264
In any LTI (Linear Time-Invariant) system, the convolution of two signals is denoted using a convolution operator, assuming all initial conditions are zero. The convolution integral can be divided into two parts: the zero-input or natural response and the zero-state or forced response, with t0 indicating the initial time.
To simplify the convolution integral, it is assumed that both the input signal and impulse response are zero for negative time values. The graphical convolution process...
264
Convolution Properties I01:20

Convolution Properties I

153
Convolution computations can be simplified by utilizing their inherent properties.
The commutative property reveals that the input and the impulse response of an LTI (Linear Time-Invariant) system can be interchanged without affecting the output:
153
Linear Approximation in Time Domain01:21

Linear Approximation in Time Domain

83
Nonlinear systems often require sophisticated approaches for accurate modeling and analysis, with state-space representation being particularly effective. This method is especially useful for systems where variables and parameters vary with time or operating conditions, such as in a simple pendulum or a translational mechanical system with nonlinear springs.
For a simple pendulum with a mass evenly distributed along its length and the center of mass located at half the pendulum's length,...
83
Properties of DTFT I01:24

Properties of DTFT I

413
In signal processing, Discrete-Time Fourier Transforms (DTFTs) play a critical role in analyzing discrete-time signals in the frequency domain. Various properties of the DTFTs such as linearity, time-shifting, frequency-shifting, time reversal, conjugation, and time scaling help understand and manipulate these signals for different applications.
The linearity property of DTFTs is fundamental. If two discrete-time signals are multiplied by constants a and b respectively, and then combined to...
413
Bewley Lattice Diagram01:12

Bewley Lattice Diagram

670
The Bewley lattice diagram, developed by L. V. Bewley, effectively organizes the reflections occurring during transmission-line transients. It visually represents how voltage waves propagate and reflect within a transmission line, making it easier to understand the complex interactions that occur.
670

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相关实验视频

Updated: Jul 9, 2025

A Photonic System for Generating Unconditional Polarization-Entangled Photons Based on Multiple Quantum Interference
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一个图像加密算法,基于双时间延迟的洛伦兹系统.

Yuzhen Zhou1, Erxi Zhu1,2, Shan Li3

  • 1College of Internet of Things Engineering, Jiangsu Vocational College of Information Technology, No.1 qianou Road, Huishan District, Jiangsu Wuxi, 214153, China.

Mathematical biosciences and engineering : MBE
|December 5, 2023
PubMed
概括

本研究介绍了一种使用双延迟混乱的新型图像加密算法,比传统方法提高了安全性和效率. 该算法提供了针对各种攻击的强有力的保护,并确保了图像无误的加密和解密.

关键词:
霍普夫分叉的双叉方式混乱的加密 混乱的加密双时间延迟的洛伦兹系统.图像加密 图像加密

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相关实验视频

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科学领域:

  • 应用数学 应用数学 应用数学
  • 计算机科学 计算机科学
  • 信息安全 信息安全

背景情况:

  • 传统的图像加密方法效率低,安全漏洞严重.
  • 基于混乱的加密提供了复杂的动态,但现有的方法有局限性.

研究的目的:

  • 提出一种新的图像加密算法,将双延迟混乱与传统技术相结合.
  • 为了提高加密效率,安全性和对抗攻击的稳定性.

主要方法:

  • 开发了一种用于图像加密的双时间延迟混乱系统.
  • 分析了使用非线性动态的双延迟的洛伦茨系统的稳定性和霍普夫分叉.
  • 使用混乱系统中的伪随机序列进行编码和扩散操作.

主要成果:

  • 拟议的算法显示了大键空间,高键灵敏度和纯文本灵敏度.
  • 实现了令人满意的混效果和无扭曲的图像加密/解密.
  • 该算法证明了对统计攻击,选择性纯文本攻击和噪音的稳定性,表现出高稳定性.

结论:

  • 基于混沌的双时间延迟图像加密算法显著改进了传统方法.
  • 该算法为图像加密应用提供了一个安全,高效和强大的解决方案.
  • 将时间延迟和其位置纳入关键空间可以提高整体安全性.