METHOD OF IDENTIFICATION

References: 14th International Multidisciplinary Scientific GeoConference SGEM 2014, www.sgem.org, SGEM2014 Conference Proceedings, ISBN 978-619-7105-20-9 / ISSN 1314-2704, June 19-25, 2014, Book 6, Vol. 1, 427-434 pp

ABSTRACT
Method of identification refers to the statistics (probability) modeling.
And in Your magazine to section «Computational and bioinformatic methods for
analysis, modeling or visualization of biological data». The difference is that the step of selecting the formulas we formalized and there-fore it is only the second stage of modeling - the choice of parameter values identified on the initial data of the generalized model or, in the special case of equation. In addi-tion, each parameter of any member has a physical meaning. This dramatically increases the
value compared to the linear regression correlation coefficient of 0.9999. History
modeling completely given additional information. Here we will show not only advantages of our method, but also possibility of identification according to aprioristic information of essentially new regularities in the form of Seed factor. Because of high definiteness of the first stage of process of statistical modeling essentially new aposteriorny information is shown. As a result «Wholecell model» method improvement for acceleration of biological opening is possible. The greatest effect gives our method without averaging and other group of basic data. The computing data set receives accurate physical sense and it increases definiteness of forecasting. The group of contradictions1 will decrease, and new opening will appear during modeling. It isn’t necessary for data1 of division on categories that was required because of application of linear regression. Therefore "Whole-cell model" addition with our wave equations would allow to give not only qualitative, but also quantitative, essence. Therefore our method of identification will allow to open the mechanism of behavior of populations of any objects.

Keywords: bricks Hilbert, the wavelet signals, generalized model, statistics, identification, verification, wave patterns At identification applied software environment CurveExpert-1.38 and CurveExpert- 1.40 (http://www.curveexpert.net).