Statistics and Its Interface

Volume 3 (2010)

Number 3

SSA of biomedical signals: A linear invariant systems approach

Pages: 345 – 355

DOI: http://dx.doi.org/10.4310/SII.2010.v3.n3.a8

Authors

N. Figueiredo (DETI, IEETA (Signal Processing Laboratory), Universidade de Aveiro, Portugal)

P. Georgieva (DETI, IEETA (Signal Processing Laboratory), Universidade de Aveiro, Portugal)

E.W. Lang (CIML Group, Biophysics, University of Regensburg, Germany)

I.M. Santos (Dep. Ciências de Educação, Universidade de Aveiro, Portugal)

A.R. Teixeira (DETI, IEETA (Signal Processing Laboratory), Universidade de Aveiro, Portugal)

A.M. Tomé (DETI, IEETA (Signal Processing Laboratory), Universidade de Aveiro, Portugal)

Abstract

Singular spectrum analysis (SSA) is considered from a linear invariant systems perspective. In this terminology, the extracted components are considered as outputs of a linear invariant system which corresponds to finite impulse response (FIR) filters. The number of filters is determined by the embedding dimension.We propose to explicitly define the frequency response of each filter responsible for the selection of informative components. We also introduce a subspace distance measure for clustering subspace models. We illustrate the methodology by analyzing Electroencephalograms (EEG).

Keywords

SSA, linear invariant systems, signal enhancement, subspace distances

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