Classification of Time-Series Data using ptSTL

被引：0

作者：

Ergurtuna, Mert ^{[1
]}

Gol, Ebru Aydin ^{[1
]}

机构：

[1] ODTU, Bilgisayar Muhendisligi, Ankara, Turkey

来源：

2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU) | 2020年

关键词：

Formula Synthesis; STL; Formal Methods; Monotonicity;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In this work, the goal is to find properties to classify time series data. These properties are expressed using past time Signal Temporal Logic (ptSTL). First, we extend monotonicity properties for signals with timed labels to signals with a single label with the purpose of optimizing parameters of template ptSTL formulas efficiently. This method optimizes a monotone criteria while keeping the complementary criteria (i.e. error) under a given bound. Then by iteratively combining optimized formulas, a classifier is generated for the time series data. Lastly, proposed method is illustrated on a case study.

引用

页数：4

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