Abstract
Using the method of generative processes, we construct a model of a random linear symmetric stable Markov process, which is a natural generalization of the Markov Gaussian process and preserves its main property: invariance with respect to arbitrary linear transformations. Methods for analyzing such processes are developed. In particular, it is proposed to use the information correlation function as a characteristic of the pair dependence between the process values at different times. This function is used to calculate the determination interval of the process.
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References
S. N. Moiseev,Geomagn. Aéronom.,37, No. 3, 107 (1997).
S. N. Moiseev,Izv. Vyssh. Uchebn. Zaved., Radiofiz.,41, No. 4, 438 (1998).
V. V. Zosimov and L. M. Lyamshev,Akust. Zh.,40, No. 5, 709 (1994).
V. S. Pugachev and I. N. Sinitsyn,Stochastic Differential Systems. Analysis and Filtering [in Russian], Nauka, Moscow (1990).
V. S. Korolyuk, N. I. Portenko, A. V. Skorokhod, and A. F. Turbin,Handbook of Probability Theory and Mathematical Statistics [in Russian], Nauka, Moscow (1985).
V. I. Tikhonov and M. A. Mironov,Markov Processes [in Russian], Sovetskoe Radio, Moscow (1977).
V. I. Tikhonov,Statistical Radio Engineering [in Russian], Radio i Svyaz’, Moscow (1982).
V. V. Gubarev,Probabilistic Models. Parts 1 and 2 [in Russian], Novosibirsk (1992).
Additional information
Voronezh State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 43, No. 3, pp. 264–270, March, 2000
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Moiseev, S.N. Markov symmetric stable processes. Radiophys Quantum Electron 43, 238–244 (2000). https://doi.org/10.1007/BF02677188
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DOI: https://doi.org/10.1007/BF02677188