Correlation Fuzzy measure of multivariate time series for signature recognition.

Journal: PloS one
PMID: 39374252

Abstract

Distinguishing different time series, which is determinant or stochastic, is an important task in signal processing. In this work, a correlation measure constructs Correlation Fuzzy Entropy (CFE) to discriminate Chaos and stochastic series. It can be employed to distinguish chaotic signals from ARIMA series with different noises. With specific embedding dimensions, we implemented the CFE features by analyzing two available online signature databases MCYT-100 and SVC2004. The accurate rates of the CFE-based models exceed 99.3%.

Authors

  • Jun Wu
    Department of Emergency, Zhuhai Integrated Traditional Chinese and Western Medicine Hospital, Zhuhai, 519020, Guangdong Province, China. quanshabai43@163.com.
  • Qingqing Wan
    Yunan Provincial Center for Disease Control and Prevention, Kunming 650022, China.
  • Zelin Zhang
    College of Veterinary Medicine, Northwest A&F University, Yangling, Shaanxi 712100, PR China.
  • Jinyu Xu
    School of Electrical and Information Engineering, Hubei University of Automotive Technology, Shi Yan, CN.
  • Wenming Cheng
    School of Economics and Management, Hubei University of Automotive Technology, Shi Yan, CN.
  • Difang Chen
    School of Mathematics, Physics and Optical Engineering, Hubei University of Automotive Technology, Shi Yan, CN.
  • Xiao Zhou
    College of Environmental Science and Engineering, Tongji University, 200092, Shanghai, China; Centre for Water Systems, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, EX4 4QF, UK.

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