Spectral and wavelet methods for the analysis of nonlinear and nonstationary time series
DOI10.1016/0016-0032(96)00011-7zbMath0903.62075OpenAlexW2080587848MaRDI QIDQ1925083
Publication date: 10 January 1999
Published in: Journal of the Franklin Institute (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/0016-0032(96)00011-7
time serieswavelet transformsnon-Gaussianityevolutionary bispectrumnonlinear signalshigher order spectratime dependent bispectrum
Nontrigonometric harmonic analysis involving wavelets and other special systems (42C40) Inference from stochastic processes and spectral analysis (62M15) Signal theory (characterization, reconstruction, filtering, etc.) (94A12)
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Cites Work
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- An introduction to bispectral analysis and bilinear time series models
- Current developments in time series modelling
- A TEST FOR LINEARITY OF STATIONARY TIME SERIES
- Fast algorithms for discrete and continuous wavelet transforms
- A sampling theorem for wavelet subspaces
- Correlation structure of the discrete wavelet coefficients of fractional Brownian motion
- Wavelet analysis and synthesis of fractional Brownian motion
- Ten Lectures on Wavelets
- The wavelet transform of stochastic processes with stationary increments and its application to fractional Brownian motion
- Wavelet approximation of deterministic and random signals: convergence properties and rates
- WAVELETS AND TIME-DEPENDENT SPECTRAL ANALYSIS
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