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相关概念视频

Linear Approximation in Frequency Domain01:26

Linear Approximation in Frequency Domain

89
Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear....
89
Reconstruction of Signal using Interpolation01:10

Reconstruction of Signal using Interpolation

194
Signal processing techniques are essential for accurately converting continuous signals to digital formats and vice versa. When a continuous signal is sampled with a period T, the resulting sampled signal exhibits replicas of the original spectrum in the frequency domain, spaced at intervals equal to the sampling frequency. To handle this sampled signal, a zero-order hold method can be applied, which creates a piecewise constant signal by retaining each sample's value until the next...
194
Downsampling01:20

Downsampling

154
When considering a sampled sequence with zero values between sampling instants, one can replace it by taking every N-th value of the sequence. At these integer multiples of N, the original and sampled sequences coincide. This process, known as decimation, involves extracting every N-th sample from a sequence, thereby creating a more efficient sequence.
The Fourier transform of the decimated sequence reveals a combination of scaled and shifted versions of the original spectrum. This...
154
Deconvolution01:20

Deconvolution

155
Deconvolution, also known as inverse filtering, is the process of extracting the impulse response from known input and output signals. This technique is vital in scenarios where the system's characteristics are unknown, and they must be inferred from the observable signals.
Deconvolution involves several mathematical techniques to derive the impulse response. One common approach is polynomial division. In this method, the input and output sequences are treated as coefficients of...
155
Properties of DTFT I01:24

Properties of DTFT I

397
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...
397
Sampling Theorem01:15

Sampling Theorem

328
In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
328

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相关实验视频

Updated: Jun 25, 2025

Demonstration of Spin-Multiplexed and Direction-Multiplexed All-Dielectric Visible Metaholograms
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哈达马德纠错代码及其在数字水印中的应用

Michael Windisch1, Jakob Wassermann1, Monica Leba2

  • 1Faculty Electronic Engineering & Entrepreneurship, University of Applied Sciences Technikum Wien, 1200 Vienna, Austria.

Sensors (Basel, Switzerland)
|May 25, 2024
PubMed
概括

一个新的增强的哈达马德纠错代码 (EHC) 显著提高了视频水印的强度,以应对高压缩. 这种新的技术在严重攻击下保护水印方面超过了Reed-Solomon代码.

关键词:
2D 哈达马德转换增强的哈达马德代码哈达马德矩阵是一个哈达马德矩阵.击距离 击距离 击距离图像基础图像的基础数字水印是指数字水印.错误纠正能力的错误纠正能力.视觉光通信 VLC 的视觉光通信

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Last Updated: Jun 25, 2025

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科学领域:

  • 通信技术 通信技术 通信技术
  • 信息安全 信息安全
  • 数字信号处理 数字信号处理

背景情况:

  • 错误纠正代码对于数字水印,无线传感器网络 (WSN) 和视觉光通信 (VLC) 来说至关重要.
  • 现有的水印方案在高压缩率 (约. 1:200) 在视频传播中常见.
  • 强大的错误纠正对于防范复杂攻击的水印完整性至关重要.

研究的目的:

  • 介绍和评估用于视频水印的新型增强的哈达马德纠错代码 (EHC).
  • 为了比较EHC与水印弹性建立的Reed-Solomon代码的有效性.
  • 展示EHC在视频水印方案中的实际应用和性能.

主要方法:

  • 开发了基于2D哈达马德基图像的增强哈达马德纠错代码 (EHC).
  • 在转换的二维基图像上实施了一种1D哈达马德解码方法,以实现增强的解码.
  • 应用了多层次的界面波段转换和低通选,用于在视频中嵌入水标.

主要成果:

  • 与Reed-Solomon代码相比,EHC在保持水印方面表现优越.
  • EHC对严重的MPEG压缩攻击具有很高的弹性.
  • 该技术显示出可能超过理论纠错能力值的潜力.

结论:

  • 增强的哈达马德纠错代码 (EHC) 是一个可行的和有效的技术,用于强大的视频水印.
  • 对于高压缩场景,EHC在传统方法 (如Reed-Solomon代码) 上具有显著的优势.
  • 未来的工作可能会探索3D EHC,以获得潜在的更好的错误纠正功能.