Parametric models of cyclostationary signals

Authors

  • I. B. Kravets Karpenko Physico-Mechanical Institute of NASU, Ukraine

DOI:

https://doi.org/10.3103/S0735272712060039

Keywords:

cyclostationary signal, periodically correlated random process, PCRP, PC process, periodic autoregression of moving average, PARMA, harmonic representation, vector autoregression of moving average, VARMA, parametric model

Abstract

The transverse resonance techniques is developed for analyzing three-layer planar structures based on micro-strip transmission line with slot resonators of complex shape in the grounding plane. Development of the techniques consists in considering higher space harmonics of current density in the strip line and mutual coupling between the slots in the grounding plane when numerically solving the boundary problem. In order to verify the techniques we conduct analysis of structures that consist of two coupled U- and symmetrical H-shaped slot resonators in the grounding plane of the micro-strip transmission line.

References

Ya. P. Dragan, V. А. Rozhkov, and I. N. Yavorskyj, Methods of Probabilistic Analysis of Rhythm of Ocean Processes (Gidrometeoizdat, Leningrad, 1987) [in Russian].

V. Yu. Mykhailyshyn, I. M. Yavors’kyi, Yu. T. Vasylyna, O. P. Drabych, and I. Yu. Isaev, “Probabilistic models and statistical methods for the analysis of vibrational signals in the problems of diagnostics of machine,” Materials Science 33, No. 5, 655 (1997).

I. Yavors’kyi, I. Kravets, I. Isaev, P. Drabych, and I. Mats’ko, “Methods for enhancement of the efficiency of statistical analysis of vibration signals from the bearing supports of turbines at thermal-electric power plants,” Materials Science 45, No. 3, 378 (2009).

І. M. Yavors’kyi, P. P. Drabych, I. B. Kravets’, І. I. Mats’ko, “Methods for vibration diagnostics of the initial stages of damage of rotation systems,” Materials Science 47, No. 2, 264 (2011).

I. Javorskyj, I. Isaev, Z. Zakrzewski, and S. P. Brooks, “Coherent Covariance Analysis of Periodically Correlated Random Processes,” Signal Processing 8, No. 1, 13 (2007).

I. Jaworski, I. Krawiec, and Z. Zakrzewski, “Koherentna i komponentna filtracja okresowo niestacjonarnych sygnalow losowych,” Przegland Telekomunikacyjny, No. 8–9, 1380 (2011).

I. Jaworskyj, J. Leskow, I. Krawets, and I. Isayev, “Gajecka Linear filtration methods for statistical analysis of periodically correlated random processes–Part I: Coherent and component methods and their generalization,” Signal Processing, http://dx.doi.org/10.1016/j.sigpro.2011.09.030.

I. Javorskyj, I. Isayev, J. Majewski, and R. Yuzefovych, “Component covariance analysis for periodically correlated random processes,” Signal Processing 90, 1083 (2010).

I. N. Yavorskyj, R. M. Yuzefovych, I. B. Kravets, and Z. Zakrzewski, “Least squares method in the statistic analysis of periodically correlated random processes,” Radioelectron. Commun. Syst. 54, No. 1, 45 (2011).

S. L. Marple, Digital Spectral Analysis with Applications (Prentice-Hall, New Jersey, 1987).

M. Pagano, “On Periodic and Multiple Autoregressions,” Annals of Statistics 6, 1310 (1978).

І. М. Yavoskyj, І. B. Kravets, and І. Yu. Isayev, “Comparison on parametric models for periodically non-stationary random processes,” Vidbir i Obrobka Informatsii, No. 31 (107), 12 (2009).

I. Javorskyj, І. Isayev, and І. Kravets, “Algorithms for Separating the Periodically Correlated Random Processes into Harmonic Series Representation,” in Proc. of 15th European Signal Processing Conf. EUSIPCO 2007, Poznan, Poland (Poznan, 2007), pp. 18571861.

I. Javorskyj, I. Kravets, and I. Isayev, “Parametric modeling for periodically correlated random processes on the basis of their harmonic representation,” J. Commun. Technol. Electronics 49, No. 11, 33 (2006).

I. Jaworskyj, J. Leskow, I. Krawets, et al., “Gajecka Linear filtration methods for statistical analysis of periodically correlated random processes–Part II: Harmonic series representation,” Signal Processing 91, 2506 (2011).

Published

2012-06-01

Issue

Section

Research Articles