@conference{10902/9442,
year = {2014},
url = {http://hdl.handle.net/10902/9442},
abstract = {We derive an estimator of the cycle period of a univariate cyclostationary process based on an information-theoretic criterion. Transforming the univariate cyclostationary process into a vector-valued wide-sense stationary process allows us to obtain the structure of the covariance matrix, which is block-Toeplitz, and its block size depends on the unknown cycle period. Therefore, we sweep the block size and obtain the ML estimate of the covariance matrix, required for the information-theoretic criterion. Since there are no closed-form ML estimates of block-Toeplitz matrices, we asymptotically approximate them as block-circulant. Finally, some numerical examples show the good performance of the proposed estimator.},
organization = {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”. The work of I. Santamaría and J. Vía was supported by the Spanish Government, Ministerio de Ciencia e Innovación (MICINN), under project RACHEL (TEC2013-47141-C4-3-R). The work of L. Scharf was supported by the Airforce Office of Scientific Research under contract FA9550-10-1-0241.},
publisher = {IEEE},
publisher = {48th Asilomar Conference on Signals, Systems and Computers, Pacific Grove, California, 2014, 1972-1976},
title = {A regularized maximum likelihood estimator for the period of a cyclostationary process},
author = {Ramírez García, David and Schreier, Peter J. and Vía Rodríguez, Javier and Santamaría Caballero, Luis Ignacio and Scharf, Louis L.},
}