Explicit formulas for the spectral characteristic and optimal linear filtration operator with a forecast for stochastic L–Markov processes are obtained using methods of spectral analysis of random processes, the theory of functions of a complex variable, and using stochastic differential-difference equations. An interesting example of an optimal filtration operator with a forecast for an L-Markov process with a quasi-rational spectral density generalizing the rational one is constructed for technical applications. It is shown that the forecast filtering operator is the sum of a linear combination of the values of the received signal at some time points and the integral of an exponentially decaying weight function.

Keywords: random process, L-Markov process, prediction filtering, spectral characteristic, filtration operator

The paper develops an algorithm for constructing an optimal lagged filtration operator for an L-Markov process. The explicit formula of the filtration operator is obtained on the basis of methods for calculating stochastic integrals and the theory of analytical functions of a complex variable using spectral analysis and the theory of L-Markov processes. An interesting example of an optimal lagged filtration operator for an L-Markov process is considered, which can be used for modeling and controlling complex stochastic systems. It is shown that this operator is represented as a linear combination of the values of the received signal and an integral with an exponentially decaying function.

Keywords: random process, L-Markov process, noise, lag filtering, spectral characteristic, filtering operator

In this paper, the problem of extrapolating a video signal with a quasi-rational spectral density, which significantly generalizes the rational density, is explicitly solved. The spectral characteristic of video signal extrapolation is constructed using the original method of A.M. Yaglom, a follower of academician A.N. Kolmogorov, who first posed the problem of extrapolation for random sequences and processes. The essence of the method consists in transferring all studies and calculations of spectral characteristics and densities from the real axis to the complex plane. The paper considers a video signal with a quasi-rational spectral density of a special type, interesting for practical applications, in which, as shown by the author using the Chebotarev and Sturm methods, it has all its roots only in an open upper half-plane.

Keywords: random process, video signal, prediction, filtering, spectral characteristic, prediction time