Title :
A regularized maximum likelihood estimator for the period of a cyclostationary process
Author :
Ramirez, David ; Schreier, Peter J. ; Via, Javier ; Santamaria, Ignacio ; Scharf, Louis L.
Author_Institution :
Signal & Syst. Theor. Group, Univ. of Paderborn, Paderborn, Germany
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.
Keywords :
Toeplitz matrices; covariance matrices; maximum likelihood estimation; ML estimation; asymptotic approximation; block size; block-Toeplitz matrices; block-circulant matrices; covariance matrix; cycle period estimator; information-theoretic criterion; regularized maximum likelihood estimator; univariate cyclostationary process period; unknown cycle period; vector-valued wide-sense stationary process; Covariance matrices; Detectors; IP networks; Maximum likelihood detection; Maximum likelihood estimation; Signal to noise ratio; Time series analysis;
Conference_Titel :
Signals, Systems and Computers, 2014 48th Asilomar Conference on
Print_ISBN :
978-1-4799-8295-0
DOI :
10.1109/ACSSC.2014.7094815
