Optimized Fuzzy Slope Entropy: A Complexity Measure for Nonlinear Time Series

Entropy has long been a subject that has attracted researchers from a diverse range of fields, including healthcare, finance, and fault detection. Slope entropy (SE) has recently been proposed as a new approach to address the shortcomings of permutation entropy (PE), which ignores magnitude information; however, SE is sensitive to parameters $\boldsymbol {\gamma }$ and $\boldsymbol {\delta }$ , and some information may be lost when segmenting symbols. The $\boldsymbol {\delta }$ , moreover, has only a limited gain on the time series classification performance of SE and increases the algorithm complexity. Considering the aforementioned limitations, this study introduces the concept of fuzzification to the…

• NS
  Natural Science Foundation of Shaanxi Province

  Award: 2022JM-337
• XU
  Xi'an University of Science and Technology

  Award: 252082218