Algorithm for the detection of changes in the dynamics of a multivariate time series via sliced cross-bispectrum

DOI10.1007/s00034-017-0577-7zbMath1427.62107OpenAlexW2616798531MaRDI QIDQ2003229

Kazimieras Pukenas

Publication date: 16 July 2019

Published in: Circuits, Systems, and Signal Processing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00034-017-0577-7

zbMATH Keywords

singular value decompositionmultivariate time series analysisHellinger divergencecross-bispectrumhigher-order spectral analysis

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Inference from stochastic processes and spectral analysis (62M15) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)

Uses Software

• Matlab

Cites Work

• Unnamed Item
• Higher-order spectrum in understanding nonlinearity in EEG rhythms
• The spectral envelope and its applications.
• Detecting changes in coupling with Granger causality method from time series with fast transient processes
• Manifold Learning for Latent Variable Inference in Dynamical Systems