5.5 Classification of data intervals based on transfer functions
Although the signal waveforms are not known a priori, there is a good understanding of
transfer functions of the GW signal and the principal noises to the Doppler. Partitioning the
data into “known-noise-like” or “other” intervals based on the noise transfer functions can be
useful. Examples of discrete-event noise classification based on transfer function were shown in
Section 4; statistical classification of data intervals based on the local acf is also possible (see,
e.g., [9
, 19]). The local spectrum or correlation function has also been used to assess the relative
importance of different noises and their stationarity from, e.g., the degree of correlation at
= T2.
