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相关概念视频

Convolution: Math, Graphics, and Discrete Signals01:24

Convolution: Math, Graphics, and Discrete Signals

845
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...
845
Deconvolution01:20

Deconvolution

548
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...
548
Convolution Properties I01:20

Convolution Properties I

556
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:
556
Convolution Properties II01:17

Convolution Properties II

580
The important convolution properties include width, area, differentiation, and integration properties.
The width property indicates that if the durations of input signals are T1 and T2, then the width of the output response equals the sum of both durations, irrespective of the shapes of the two functions. For instance, convolving two rectangular pulses with durations of 2 seconds and 1 second results in a function with a width of 3 seconds.
The area property asserts that the area under the...
580
Encoding01:19

Encoding

748
Information enters the brain through encoding, which is the input of information into the memory system. Once sensory information is received from the environment, the brain labels or codes it. The information is then organized with similar information and connected to existing concepts. Encoding occurs through automatic processing and effortful processing.
Automatic processing involves the encoding of details like time, space, frequency, and the meaning of words, usually done without conscious...
748
Extraction: Partition and Distribution Coefficients01:14

Extraction: Partition and Distribution Coefficients

4.6K
The distribution law or Nernst's distribution law is the law that governs the distribution of a solute between two immiscible solvents. This law, also known as the partition law, states that if a solute is added to the mixture of two immiscible solvents at a constant temperature, the solute is distributed between the two solvents in such a way that the ratio of solute concentrations in the solvents remains constant at equilibrium.
For extracting a solute from an aqueous phase into an...
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相关实验视频

Updated: Jan 17, 2026

Decoding Natural Behavior from Neuroethological Embedding
08:00

Decoding Natural Behavior from Neuroethological Embedding

Published on: October 3, 2025

605

信息集对卷积代码的解码

Niklas Gassner1, Julia Lieb2, Abhinaba Mazumder1

  • 1Institute of Mathematics, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.

Designs, codes, and cryptography
|September 18, 2025
PubMed
概括
此摘要是机器生成的。

研究人员开发了解码卷积代码的新框架,使得基于代码的系统的加密分析成为可能. 这种方法成功地恢复了McEliece加密系统变异中的高百分比错误,证明了对卷积代码加密的实际攻击.

关键词:
编码理论编码理论卷积代码 卷积代码是指卷积代码.密码学 密码学 密码学 密码学信息集解码信息集的解码.

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Automated Analysis of C. elegans Fluorescence Images using SegElegans
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Last Updated: Jan 17, 2026

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Automated Analysis of C. elegans Fluorescence Images using SegElegans
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Automated Analysis of C. elegans Fluorescence Images using SegElegans

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科学领域:

  • 密码学 密码学 密码学 密码学
  • 编码理论编码理论
  • 计算机科学 计算机科学

背景情况:

  • 基于代码的密码学依赖于解码一般线性代码的难度.
  • 卷积码是某些加密系统中使用的一种特定类型的代码.
  • 对于这些系统而言,现有的加密分析方法可能是计算密集的.

研究的目的:

  • 为卷积代码提供一个通用的解码框架.
  • 应用此框架用于基于代码的加密系统的加密分析.
  • 评估成功概率,并为信息集解码中的参数选择提供工具.

主要方法:

  • 开发了对卷积代码的通用解码框架.
  • 将框架应用于信息集解码.
  • 分析了成功概率和对解码的变量选择.
  • 在两个特定的加密系统上使用卷积代码进行了加密分析.

主要成果:

  • 在10小时内成功恢复了McEliece加密系统变化的约74%的错误.
  • 提供了恢复另一个加密系统80%的错误的实验证据 (Almeida等). 在相当于~70位安全的时间里.
  • 证明了对加密系统利用卷积代码的实际攻击.

结论:

  • 拟议的解码框架有效用于使用卷积代码加密分析基于代码的系统.
  • 该框架提供了攻击现有加密系统的实用方法,影响了密钥大小和安全估计.
  • 这项工作为理解和潜在地打破卷积代码基础密码学提供了有价值的工具.