Probability Distributions of Means of IA and IF for Gaussian Noise and Its Application to an Anomaly Detection

DOI10.1142/S2424922X18500067zbMath1402.62208MaRDI QIDQ4686467

Masato Kaneyama, Kazuki Sakai, Hirotaka Takahashi, Ken-Ichi Oohara

Publication date: 10 October 2018

Published in: Advances in Data Science and Adaptive Analysis (Search for Journal in Brave)

zbMATH Keywords

anomaly detectionPearson distributionHilbert-Huang transform

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Cites Work

• A study of the characteristics of white noise using the empirical mode decomposition method
• The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
• One or Two Frequencies? The Empirical Mode Decomposition Answers
• Applications of Hilbert–Huang transform to non‐stationary financial time series analysis
• Hilbert–Huang Transform and Its Applications

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