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Classification of Systems-I01:26

Classification of Systems-I

154
Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:
154
Classification of Systems-II01:31

Classification of Systems-II

119
Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
119
Aggregates Classification01:29

Aggregates Classification

289
Aggregate classification is generally based on its size, petrographic characteristics, weight, and source. Size classification ranges from coarse to fine aggregates, defined by the size of the particles. Coarse aggregates are particles that do not pass through ASTM sieve No. 4, and aggregates that pass through the sieve are fine aggregates.
Petrographic classification groups aggregates based on common mineralogical characteristics. Some of the common mineral groups found in aggregates are...
289
Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

227
Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:
227
Routh-Hurwitz Criterion II01:19

Routh-Hurwitz Criterion II

156
In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first...
156
Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

102
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
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相关实验视频

Updated: May 9, 2025

Network Analysis of Foramen Ovale Electrode Recordings in Drug-resistant Temporal Lobe Epilepsy Patients
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一个基于边缘灵敏度的梯度攻击在图形等态网络上的图形分类问题.

Srinitish Srinivasan1, Chandraumakantham OmKumar2

  • 1School of Computer Science and Engineering, Vellore Institute of Technology, Chennai, India.

Scientific reports
|April 29, 2025
PubMed
概括

研究人员为图形神经网络 (GNN) 开发了一种新的白盒梯度攻击. 这种攻击显著降低了GNN在图形分类任务上的性能,突出了当前模型的漏洞.

科学领域:

  • 机器学习 机器学习
  • 图形神经网络的神经网络
  • 敌对的攻击 敌对的攻击

背景情况:

  • 图形神经网络 (GNN) 在建模关系方面非常强大,但缺乏理想的欧几里德空间表示.
  • 虽然GNN容易受到敌对攻击,但对潜伏空间嵌入的梯度式攻击尚未得到充分探索.

研究的目的:

  • 提出一种新的白盒基于梯度的对抗性攻击,用于使用对比的潜伏空间表示的GNN.
  • 开发一个强大的GNN模型,学习光谱和空间图形属性,考虑等态属性.

主要方法:

  • 开发了一个基于白盒梯度的攻击,针对GNN潜伏空间嵌入.
  • 构建了一个强大的基GNN模型,包含光谱,空间和异态性质.
  • 在四个分子性质预测数据集上验证了GNN模型.

主要成果:

  • 拟议的GNN模型在评估的基于LLM的架构中表现优于75%以上.
  • 对抗性攻击使GNN模型在图形分类任务中的性能平均下降了25%.

结论:

  • 该研究引入了针对GNN的新对抗性攻击策略,解决了现有文献中的差距.
  • 这些发现证明了强大的GNN对潜伏空间攻击的易感性,并为开发更具弹性模型提供信息.

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