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Universal Journal of Applied Mathematics Vol. 2(3), pp. 141 - 147
DOI: 10.13189/ujam.2014.020304
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Modeling of Stochastic Processes in L_p(T) Using Orthogonal Polynomials

Oleksandr Mokliachuk ^*
National Technical University of Ukraine "Kyiv Polytechnic Institute", Kiev, Ukraine

ABSTRACT

In this paper, models that approximate stochastic processes from the space Sub_蠁(惟) with given reliability and accuracy in L_p(T) are considered for some specific functions 蠁(t). For processes that are decomposited in series using orthonormal bases, such models are constructed in the case where elements of such decomposition cannot be found explicitly.

KEYWORDS
Models of Stochastic Processes, 蠁-sub- Gaussian Processes, Orthogonal Polynomials

Cite This Paper in IEEE or APA Citation Styles
(a). IEEE Format:
[1] Oleksandr Mokliachuk , "Modeling of Stochastic Processes in L_p(T) Using Orthogonal Polynomials," Universal Journal of Applied Mathematics, Vol. 2, No. 3, pp. 141 - 147, 2014. DOI: 10.13189/ujam.2014.020304.

(b). APA Format:
Oleksandr Mokliachuk (2014). Modeling of Stochastic Processes in L_p(T) Using Orthogonal Polynomials. Universal Journal of Applied Mathematics, 2(3), 141 - 147. DOI: 10.13189/ujam.2014.020304.