---
res:
bibo_abstract:
- Recently, a generalization of the magnitude squared coherence (MSC) spectrum for
more than two random processes has been proposed. The generalized MSC (GMSC) spectrum
definition, which is based on the largest eigenvalue of a matrix containing all
the pairwise complex coherence spectra, provides a frequency-dependent measure
of the linear relationship among several stationary random processes. Moreover,
it can be easily estimated by solving a generalized eigenvalue problem. In this
paper we apply the GMSC spectrum for detecting the presence of a common signal
from a set of linearly distorted and noisy observations. Specifically, the new
statistic for the multiple-channel detection problem is the integral of the square
root of the GMSC, which can be estimated as the sum of the $P$ largest generalized
canonical correlations (typically $P=1$ is enough in practice). Unlike previous
approaches, the new statistic implicitly takes into account the spectral characteristics
of the signal to be detected (e.g., its bandwidth). Finally, the performance of
the proposed detector is compared in terms of its receiver operating characteristic
(ROC) curve with the generalized coherence (GC) showing a clear improvement in
most scenarios.@eng
bibo_authorlist:
- foaf_Person:
foaf_givenName: D.
foaf_name: Ramírez, D.
foaf_surname: Ramírez
- foaf_Person:
foaf_givenName: J.
foaf_name: Vía, J.
foaf_surname: Vía
- foaf_Person:
foaf_givenName: I.
foaf_name: Santamaría, I.
foaf_surname: Santamaría
dct_date: 2008^xs_gYear
dct_title: Multiple-Channel Signal Detection using the Generalized Coherence spectrum@
...