跳到正文
arXiv cs.AI· Roderick Bloem, Benedikt Maderbacher, Cristinel Mateis, Dejan Ni\v{c}kovi\'{c}, Sergii Tkachov, Bj\"orn Ziegler·· 14 小时前AI 评分20

结合形式化规范与数据驱动信号分析的混合方法

Formal Specifications with Data-Driven Signal Analysis

AI 导读

研究者提出一种融合规范与数据驱动技术的混合方法,用于分析和监控实值信号:用带区间运算的正则表达式定位信号中的关注区域,用经典信号处理方法提取语义特征,再用半监督机器学习推断区分正常与故障行为的复杂关系。从正常行为数据中学到的关系可自动检测同一系统或其变体的异常行为,并在电压调节器上验证了有效性。

正文 · 原文

View PDF HTML (experimental)

Abstract:Developing analog and hybrid systems requires substantial domain knowledge that is hard to articulate in a formal specification; without additional effort, this domain knowledge is also inaccessible to machine learning methods. We propose a hybrid approach for analyzing and monitoring real-valued signals that integrates specification-based and data-driven techniques. We use regular expressions with interval operations to identify regions of interest in a signal, classical signal processing methods to extract semantically meaningful features, and semi-supervised machine learning to infer complex relationships that distinguish correct from faulty behaviors. The relationships learned from normal behavior data can automatically detect incorrect behavior in the same system or variants thereof. We evaluate the method on a voltage regulator, demonstrating its effectiveness in detecting undesired system behaviors.
Subjects: Artificial Intelligence (cs.AI); Machine Learning (cs.LG)
Cite as: arXiv:2610.39007 [cs.AI]
  (or arXiv:2610.39007v1 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2610.39007

arXiv-issued DOI via DataCite

Submission history

From: Cristinel Mateis [view email]
[v1] Wed, 28 Oct 2026 22:34:17 UTC (205 KB)

来源:arXiv cs.AI · arxiv.org