@article {532,
	title = {Testing Equality of Multiple Power Spectral Densities},
	journal = {IEEE Transactions on Signal Processing},
	volume = {66},
	year = {2018},
	month = {December},
	pages = {6268-6280},
	abstract = {This work studies the existence of optimal invariant detectors for determining whether P multivariate processes have the same power spectral density (PSD). This problem finds application in multiple fields, including physical layer security and cognitive radio. For Gaussian observations, we prove that
the optimal invariant detector, i.e., the uniformly most powerful invariant test (UMPIT), does not exist. Additionally, we consider the challenging case of close hypotheses, where we study the
existence of the locally most powerful invariant test (LMPIT). The LMPIT is obtained in closed form only for univariate signals. In the multivariate case, it is shown that the LMPIT does not exist.
However, the corresponding proof naturally suggests one LMPITinspired detector, which outperforms previously proposed detectors.},
	issn = {1053-587X},
	doi = {10.1109/TSP.2018.2875884},
	author = {Ram{\'\i}rez, David and Romero, Daniel and V{\'\i}a, Javier and L{\'o}pez-Valcarce, Roberto and Santamar{\'\i}a, Ignacio}
}
@conference {510,
	title = {Locally Optimal Invariant Detector for Testing Equality of Two Power Spectral Densities},
	booktitle = { IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
	year = {2018},
	month = {April},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Calgary, Canada},
	author = {Ram{\'\i}rez, David and Romero, Daniel and V{\'\i}a, Javier and L{\'o}pez-Valcarce, Roberto and Santamar{\'\i}a, Ignacio}
}
@conference {326,
	title = {Detection of Gaussian Signal in Unknown Time-Varying Channels},
	booktitle = {IEEE Statistical Signal Processing Workshop (SSP 2012)},
	year = {2012},
	month = {August},
	address = {Ann Arbor, USA},
	author = {Romero, Daniel and V{\'\i}a, Javier and L{\'o}pez-Valcarce, Roberto and Santamar{\'\i}a, Ignacio}
}
