@conference{10902/9441,
year = {2014},
url = {http://hdl.handle.net/10902/9441},
abstract = {We derive the generalized likelihood ratio test (GLRT) for detecting cyclostationarity in scalar- valued time series. The main idea behind our approach is Gladyshev’s relationship, which states that when the scalar-valued cyclostationary signal is blocked at the known cycle period it produces a vectorvalued wide-sense stationary (WSS) process. This result amounts to saying that the covariance matrix of the vector obtained by stacking all observations of the time series is block-Toeplitz if the signal is cyclostationary, and Toeplitz if the signal is wide-sense stationary. The derivation of the GLRT requires the maximum likelihood estimates of Toeplitz and block-Toeplitz matrices. This can be managed asymptotically (for large number of samples) exploiting Szegö’s theorem and its generalization for vector-valued processes. Simulation results show the good performance of the proposed GLRT.},
organization = {The work of L. Scharf was supported by the Airforce Office of Scientific Research under contract FA9550-10-1-0241. The work of I. Santamaría and J. Vía was supported by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under project COSIMA (TEC2010-19545-C04-03) and project COMONSENS (CSD2008-00010, CONSOLIDER-INGENIO 2010 Program). The work of P. Schreier was supported by the Alfried Krupp von Bohlen und Halbach Foundation, under its program “Return of German scientists from abroad.},
publisher = {IEEE},
publisher = {IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2014),    Florence, Italy, 2014, 3415-3419},
title = {An asymptotic GLRT for the detection of cyclostationary signals},
author = {Ramírez García, David and Scharf, Louis L. and Vía Rodríguez, Javier and Santamaría Caballero, Luis Ignacio and Schreier, Peter J.},
}