Correlation Fuzzy measure of multivariate time series for signature recognition

Correlation Fuzzy measure of multivariate time series for signature recognition

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 ARIM...

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Veröffentlicht in:PloS one 2024-10, Vol.19 (10), p.e0309262
Hauptverfasser: Wu, Jun, Wan, Qingqing, Zhang, Zelin, Xu, Jinyu, Cheng, Wenming, Chen, Difang, Zhou, Xiao
Format: Artikel
Sprache:eng
Schlagworte:
Algorithms
Autoregressive models
Biology and Life Sciences
Computer and Information Sciences
Correlation
Determinism
Embedding
Engineering and Technology
Entropy
Evaluation
Factorial experiments
Fuzzy algorithms
Fuzzy Logic
Fuzzy sets
Fuzzy systems
Humans
Mathematical research
Multivariate Analysis
Normal distribution
Object recognition (Computers)
Pattern recognition
Physical Sciences
Research and Analysis Methods
Signal processing
Signal Processing, Computer-Assisted
Stochasticity
Time Factors
Time measurement
Time series
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Zusammenfassung: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%.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0309262