Modeling of the scattering of electromagnetic waves by cavities of elliptic cross section

Based on the mode method, we develop a technique for calculation of the effective scattering area (ESA) of a perfectly conducting cavity of elliptic cross section with the rear wall covered by a radio-absorbing coating (RAC) of constant thickness. In the case where the incident electromagnetic wave is E-polarized, we numerically calculate the angular dependences of the monostatic ESA of an elliptic cavity with and without the RAC. The results of calculations are compared with the obtained experimental data. Voronezh State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 43, No. 5, pp. 426–432, May, 2000.     

Optimum reception of a pulsed optical signal with unknown time of arrival

We obtain and compare the maximum-likelihood and Bayesian algorithms for detecting a signal and measuring its arrival time. Using computer statistical simulation, we test the robustness of the synthesized algorithms and determine the validity ranges of the asymptotic formulas for their characteristics. Voronezh State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 42, No. 12, pp. 1201–1212, December 1999.     

Distribution function of the sporadic E-layer screening frequency

The distribution function of the sporadic E-layer screening frequency is derived using the techniques of mathematical statistics and the physical theory of sporadic E-layer formation. The function is compared to the empirical distribution functions known from literature. The best correlation of the obtained distribution and experimental data is shown.Voronezh State University. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 34, No. 8, pp. 872–878, August, 1991.     

Optimal reception of a rectangular pulse with unknown appearance and disappearance times

We obtain the maximum-likelihood and optimum (Bayesian) algorithms for detecting and estimating the appearance and disappearance times of a rectangular pulse against the white-noise background. Rigorous expressions for the characteristics of the maximum-likelihood algorthms are found. The characteristics of the Bayesian algorithms are obtained using computer simulations. Voronezh State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 43, No. 3, pp. 271–282, March, 2000     

Calculating pair interaction potentials for phosphorus and gallium atoms

The Hartree-Fock-Roothaan ab initio self-consistent average field method has been used in calculating the pair interaction potentials for atoms in the P₂ and GaP molecules. The gallium and phosphorus atoms are considered in their ground states. The calculations agree well with experiment. Voronezh State Technical University, Voronezh. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, Vol. 42, No. 1, pp. 95–99, January, 1999.     

Markov symmetric stable processes

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. Voronezh State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 43, No. 3, pp. 264–270, March, 2000     

Probability characteristics of the absolute maximum of generalized rayleigh stochastic process

We obtain the limiting laws of distribution of the absolute maximum of the generalized Rayleigh random process. Using the methods of statistical modeling, we show that the asymptotic approximations are in good agreement with the actual distributions over a wide range of parameters of the random process. Voronezh State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 42, No. 12, pp. 1213–1222, September 1999.     

Preservation of long range temporal correlations under extreme random dilution

Many natural time series exhibit long range temporal correlations that may be characterized by power-law scaling exponents. However, in many cases, the time series have uneven time intervals due to, for example, missing data points, noisy data, and outliers. Here we study the effect of randomly missing data points on the power-law scaling exponents of time series that are long range temporally correlated. The Fourier transform and detrended fluctuation analysis (DFA) techniques are used for scaling exponent estimation. We find that even under extreme dilution of more than 50%, the value of the scaling exponent remains almost unaffected. Random dilution is also applied on heart interbeat interval time series. It is found that dilution of 70%-80% of the data points leads to a reduction of only 8% in the scaling exponent; it is also found that it is possible to discriminate between healthy and heart failure subjects even under extreme dilution of more than 90%.     

Ordinal pattern and statistical complexity analysis of daily stream flow time series

When calculating the Bandt and Pompe ordinal pattern distribution from given time series at depth D, some of the D! patterns might not appear. This could be a pure finite size effect (missing patterns) or due to dynamical properties of the observed system (forbidden patterns). For pure noise, no forbidden patterns occur, contrary to deterministic chaotic maps. We investigate long time series of river runoff for missing patterns and calculate two global properties of their pattern distributions: the Permutation Entropy and the Permutation Statistical Complexity. This is compared to purely stochastic but long-range correlated processes, the k-noise (noise with power spectrum f ^?k ), where k is a parameter determining the strength of the correlations. Although these processes closely resemble runoff series in their correlation behavior, the ordinal pattern statistics reveals qualitative differences, which can be phrased in terms of missing patterns behavior or the temporal asymmetry of the observed series. For the latter, an index is developed in the paper, which may be used to quantify the asymmetry of natural processes as opposed to artificially generated data.     

Scattering of an electromagnetic wave by a radially inhomogenous plasma cylinder with electron density fluctuations

Voronezh Polytechnical Institute. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 33, No. 9, pp. 1055–1059, September, 1990.     

Generalized unscented Kalman filtering based radial basis function neural network for the prediction of ground radioactivity time series with missing data

On the assumption that random interruptions in the observation process are modeled by a sequence of independent Bernoulli random variables, we firstly generalize two kinds of nonlinear filtering methods with random interruption failures in the observation based on the extended Kalman filtering (EKF) and the unscented Kalman filtering (UKF), which were shortened as GEKF and GUKF in this paper, respectively. Then the nonlinear filtering model is established by using the radial basis function neural network (RBFNN) prototypes and the network weights as state equation and the output of RBFNN to present the observation equation. Finally, we take the filtering problem under missing observed data as a special case of nonlinear filtering with random intermittent failures by setting each missing data to be zero without needing to pre-estimate the missing data, and use the GEKF-based RBFNN and the GUKF-based RBFNN to predict the ground radioactivity time series with missing data. Experimental results demonstrate that the prediction results of GUKF-based RBFNN accord well with the real ground radioactivity time series while the prediction results of GEKF-based RBFNN are divergent.     

Correlation and complexity analysis of well logs via Lyapunov, Hurst, Lempel-Ziv and neural network algorithms

Well logs produce a wealth of data that can be used to evaluate the production capacity of oil and gas fields. These data are usually concerned with depth series of petrophysical quantities such as the sonic transient time, gamma emission, deep induction resistivity, neutron porosity and bulk density. Here, we perform a correlation and complexity analysis of well log data from the Namorado’s school field using Lyapunov, Hurst, Lempel-Ziv and neural network algorithms. After identifying the most correlated and complex series, we demonstrate that well log data estimates can be confidently performed by neural network algorithms either to complete missing data or to infer complete well logs of a specific quantity.     

A time series analysis and a non-homogeneous Poisson model with multiple change-points applied to acoustic data

High levels of the so-called community noise may produce hazardous effect on the health of a population exposed to them for large periods of time. Hence, the study of the behaviour of those noise measurements is very important. In this work we analyse that in terms of the probability of exceeding a given threshold level a certain number of times in a time interval of interest. Since the datasets considered contain missing measurements, we use a time series model to estimate the missing values and complete the datasets. Once the data is complete, we use a non-homogeneous Poisson model with multiple change-points to estimate the probability of interest. Estimation of the parameters of the models are made using the usual time series methodology as well as the Bayesian point of view via Markov chain Monte Carlo algorithms. The models are applied to data obtained from two measuring sites in Messina, Italy.     

Change in the polarization of a plane electromagnetic wave when reflected by a smooth layer of collisionless plasma

Voronezh Wood Technology Institute. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 33, No. 8, pp. 912–918, August, 1990.     

Functional Kernel Density Estimation: Point and Fourier Approaches to Time Series Anomaly Detection

We present an unsupervised method to detect anomalous time series among a collection of time series. To do so, we extend traditional Kernel Density Estimation for estimating probability distributions in Euclidean space to Hilbert spaces. The estimated probability densities we derive can be obtained formally through treating each series as a point in a Hilbert space, placing a kernel at those points, and summing the kernels (a “point approach”), or through using Kernel Density Estimation to approximate the distributions of Fourier mode coefficients to infer a probability density (a “Fourier approach”). We refer to these approaches as Functional Kernel Density Estimation for Anomaly Detection as they both yield functionals that can score a time series for how anomalous it is. Both methods naturally handle missing data and apply to a variety of settings, performing well when compared with an outlyingness score derived from a boxplot method for functional data, with a Principal Component Analysis approach for functional data, and with the Functional Isolation Forest method. We illustrate the use of the proposed methods with aviation safety report data from the International Air Transport Association (IATA).     

Investigation of the conditions for feeding filamentary silicon crystals,growing in a reactor with hot walls

An estimate of the factors which influence the rate of growth of filamentary silicon crystals in a standard chloride system using a quartz reactor with hot walls is given. It is shown that a diffusion form of crystallization is observed under the conditions investigated.Voronezh State Technical University. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 10, pp. 22–26, October, 1995.     

Accuracy of ES-layer screening-frequency forecasting

The accuracy of forecasts of the screening frequency of the middle-latitude sporadic-E layer is analyzed. It is shown that the accuracy of screening-frequency forecasts is a function of time of day and the a priori screening frequencies used in the forecast.Voronezh State University. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 36, No. 2, pp. 121–125, February, 1993.     

A combined method using the plane-wave concept for estimating the SCS of half-open complex-shaped cavities with a radio-absorbing coating

We present a combined method for estimating the scattering cross section (SCS) of half-open complex-shaped cavities with a radio-absorbing coating (RAC), which is based on the combined boundary-integral modal method and the plane-wave concept. Calculating the SCS of a cavity, we use experimental dependences of the absolute value and the phase of the reflection factor of the RAC, which is located on a plane, ideally conducting surface, on the electromagnetic wave incidence angle. The results of calculation of the SCS of a half-open complex-shaped cavity with a RAC using the above combined method agree with the experimental data obtained. Central Research Institute, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 40, No. 5, pp. 652–661, May, 1997.     

Probability laws of distribution of the ionization maximum of theE s layer with allowance for the boundary conditions

We consider the boundary conditions which prohibit the appearance of values of electron density of the E_s layer below the background level and above the limiting permissible level. On the basis of the Cauchy distribution, for each boundary condition we obtain the 1D probability laws of distribution of the maximum electron density of the E_s layer. These laws are verified against experimental data. State University, Voronezh, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 41, No. 4, pp. 438–445, April, 1998.     

Detection of extended radio source in noise

The generalized maximum-likelihood method is used to synthesize the algorithm for detecting an extended source of random radio emission with unknown distribution of brightness across the radiating surface. We propose a simple model for the unknown function of spatial distribution of the energy brightness. Voronezh State University, Russia. Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Radiofizika, Vol. 42, No. 4, pp. 394–399, April 1999.