TY - JOUR
T1 - Intrinsic Entropy
T2 - A Novel Adaptive Method for Measuring the Instantaneous Complexity of Time Series
AU - Huang, Po Hsun
AU - Hsiao, Tzu Chien
N1 - Publisher Copyright:
© 1994-2012 IEEE.
PY - 2023/2/13
Y1 - 2023/2/13
N2 - The determination of appropriate parameters and an appropriate window size in most entropy-based measurements of time-series complexity is a challenging problem. Inappropriate settings can lead to the loss of intrinsic information within a time series. Therefore, two parameter-free methods, namely the intrinsic entropy (IE) and ensemble IE (eIE) methods, are proposed in this paper. The eIE method requires two parameters, which can be easily determined through an orthogonality test. The proposed approaches can measure instantaneous complexity; thus, they do not require a predetermined window size. White noise and three other varieties of colored noise were used to test the stability of the proposed methods, and five types of synthetic signals and logistic maps were applied for measuring instantaneous complexity and regularity. The results revealed that the IE and eIE methods exhibit satisfactory stability. Both methods provide point-by-point entropy measures for time series. The eIE method is useful for measuring the complexity of frequency and amplitude modulation. Furthermore, the periodicity of time series can be detected using the two proposed methods.
AB - The determination of appropriate parameters and an appropriate window size in most entropy-based measurements of time-series complexity is a challenging problem. Inappropriate settings can lead to the loss of intrinsic information within a time series. Therefore, two parameter-free methods, namely the intrinsic entropy (IE) and ensemble IE (eIE) methods, are proposed in this paper. The eIE method requires two parameters, which can be easily determined through an orthogonality test. The proposed approaches can measure instantaneous complexity; thus, they do not require a predetermined window size. White noise and three other varieties of colored noise were used to test the stability of the proposed methods, and five types of synthetic signals and logistic maps were applied for measuring instantaneous complexity and regularity. The results revealed that the IE and eIE methods exhibit satisfactory stability. Both methods provide point-by-point entropy measures for time series. The eIE method is useful for measuring the complexity of frequency and amplitude modulation. Furthermore, the periodicity of time series can be detected using the two proposed methods.
KW - Empirical mode decomposition (EMD)
KW - instantaneous complexity
KW - intrinsic entropy (IE)
KW - signal regularity
UR - http://www.scopus.com/inward/record.url?scp=85149379811&partnerID=8YFLogxK
U2 - 10.1109/LSP.2023.3244508
DO - 10.1109/LSP.2023.3244508
M3 - Article
AN - SCOPUS:85149379811
SN - 1070-9908
VL - 30
SP - 160
EP - 164
JO - IEEE Signal Processing Letters
JF - IEEE Signal Processing Letters
ER -