Mathematical framework for pseudo-spectra of linear stochastic difference equations
2013
Although spectral analysis of stationary stochastic processes has solid mathematical foundations, this is not always so for some non-stationary cases. Here, we establish a rigorous mathematical extension of the classic Fourier spectrum to the case in which there are AR roots in the unit circle, ie, the transfer function of the linear time-invariant filter has poles on the unit circle. To achieve it we: embed the classical problem in a wider framework, the Rigged Hilbert space, extend the Discrete Time Fourier Transform and defined a new Extended Fourier Transform pair pseudo-covariance function/pseudo-spectrum. Our approach is a proper extension of the classical spectral analysis, within which the Fourier Transform pair auto-covariance function/spectrum is a particular case. Consequently spectrum and pseudo-spectrum coincide when the first one is defined.
Keywords:
- Discrete Fourier series
- Discrete-time Fourier transform
- Discrete Fourier transform (general)
- Non-uniform discrete Fourier transform
- Fourier transform
- Fractional Fourier transform
- Fourier inversion theorem
- Discrete mathematics
- Mathematics
- Mathematical analysis
- Least-squares spectral analysis
- Discrete Fourier transform
- Z-transform
- Correction
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