Publication Date:
2004
abstract:
In this paper the orthogonal decomposition is used in order to reconstruct
the noiseless component of a temporal stochastic process. For weakly stationary
processes, the proposed methodology is based on the joint application of
the spectral analysis in the frequency domain (Fourier analysis) and in the time
domain (Karhunen Lo´eve expansion). For non stationary processes the orthogonal
decomposition is realized in the wavelet domain.
the noiseless component of a temporal stochastic process. For weakly stationary
processes, the proposed methodology is based on the joint application of
the spectral analysis in the frequency domain (Fourier analysis) and in the time
domain (Karhunen Lo´eve expansion). For non stationary processes the orthogonal
decomposition is realized in the wavelet domain.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
List of contributors:
Fontanella, Lara; Granturco, M.
Book title:
Advances in Multivariate Data Analysis