alexa Identification of Wave Regularities According to Statistical Data of Parameters of 24 Pulsars
ISSN: 2090-0902

Journal of Physical Mathematics
Open Access

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Research Article

Identification of Wave Regularities According to Statistical Data of Parameters of 24 Pulsars

Mazurkin PM*

Doctor of Engineering, Academician of Russian Academy of Natural History and Russian Academy of Natural Sciences, Volga State University of Technology, Russia

*Corresponding Author:
Mazurkin PM
Doctor of Engineering, professor
Academician of Russian Academy
of Natural History and Russian Academy of
Natural Sciences, Volga State
University of Technology
Russia
Tel: 2156561646
E-mail: [email protected]

Received Date: November 14, 2016 Accepted Date: November 28, 2016 Published Date: November 30, 2016

Citation: Mazurkin PM (2016) Identification of Wave Regularities According to Statistical Data of Parameters of 24 Pulsars. J Phys Math 7: 206. doi: 10.4172/2090-0902.1000206

Copyright: © 2016 Mazurkin PM. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

 

Abstract

The method of identification is shown on the example of tabular these measurements of six parameters at 24 pulsars. The equations of a trend and oscillatory indignations on the basis of steady laws on the generalized wave function in the form of an asymmetric wavelet signal with variables of amplitude and the period of fluctuation are received. On the remains it is possible to receive a set of microfluctuations and to bring identification to an error of measurements. Schedules of components of the generalized model of a wavelet signal allow to see visually a picture of mutual influence of all six parameters of pulsars. On the revealed equations it is possible to carry out the amplitude-frequency analysis. Quality of basic data is estimated by rank distributions of values of parameters of pulsars. Thus ranging of values of parameters on a preference preorder vector "better→worse" is carried out in the beginning, the rating of pulsars is formed further.

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