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The effectiveness of communication and data transmission systems (CSiPS), which are an integral part of modern systems in almost any field of science and technology, largely depends on the stability of the frequency of the generated signals. The signals generated in the CSiPD can be considered as processes, the frequency of which changes under the influence of a combination of external influences. Changing the frequency of the signals leads to a decrease in the signal-tonoise ratio (SNR) and, consequently, a deterioration in the characteristics of the signal-to-noise ratio, such as the probability of a bit error and bandwidth. It is most convenient to consider the description of such changes in the frequency of signals as random processes, the apparatus of which is widely used in the construction of mathematical models describing the functioning of systems and devices in various fields of science and technology. Moreover, in many cases, the characteristics of a random process, such as the distribution law, mathematical expectation, and variance, may be unknown or known with errors that do not allow us to obtain estimates of the signal parameters that are acceptable in accuracy. The article proposes an algorithm for solving the problem of determining the characteristics of a random process (signal frequency) based on a set of samples of its frequency, allowing to determine the sample mean, sample variance and the distribution law of frequency deviations in the general population. The basis of this algorithm is the comparison of the values of the observed random process measured over a certain time interval with a set of the same number of random values formed on the basis of model distribution laws. Distribution laws based on mathematical models of these systems and devices or corresponding to similar systems and devices can be considered as model distribution laws. When forming a set of random values for the accepted model distribution law, the sample mean value and variance obtained from the measurement results of the observed random process are used as mathematical expectation and variance. The feature of the algorithm is to compare the measured values of the observed random process ordered in ascending or descending order and the generated sets of values in accordance with the accepted models of distribution laws. The results of mathematical modeling illustrating the application of this algorithm are presented.

This paper proposes an architectural solution for organizing a convolutional neural network (CNN) oriented towards hardware implementation on edge devices under limited resources. To this goal, an approach to compressing spectrograms to a given size (28 × 28) is proposed using discretization, monoconversion, windowed Fourier transform, and two-dimensional interpolation. A balanced convolution procedure is developed based on compact convolutional filters, the size of which provides the balance between computational complexity and accuracy required for edge devices. An algorithm that enables convolution operations and calculation of the error function gradient in the convolutional layer in a single cycle ensuring increased performance in both inference and training modes of the CNN is proposed. The tradeoff between network trainability and its resistance to overfitting is optimized by applying the Dropout regularization method with a dropout coefficient of 0.5 for the fully connected layer.

The effectiveness of the proposed solution was demonstrated using the example of recognizing audio spectrograms of car and airplane engine sounds. The CNN was trained on a balanced dataset consisting of 7160 audio recordings. The trained network demonstrated high recognition accuracy (95%), low loss values (< 0.2), and balanced precision/recall/F-metric, demonstrating the effectiveness of the developed CNN model.

A new flow modeling method on unstructured grid was proposed. As a basis system this method used quasi-hydro-dynamic equations. The finite volume method vas used for solving these equations. The Delaunay triangulation was used for constructing mesh. This proposed method was tested in modeling of incompressible flow through a channel with complex profile. The acquired results showed that the proposed method could be used in flow modeling in unstructured grid.

The first solution for wind-induced flow of homogeneous fluid was found in 1905 by Ekman and it involved the sum of two components: the drift current determined by wind stress and the geostrophic current determined by slope of the free surface. Drift current is defined by the specific formula and can be easily analyzed. In order to find the geostrophic current it is necessary to solve an elliptic type equation in the area bounded by coastline and it is a more difficult problem. In this paper examples of areas and wind stresses are given for the case when the equations for finding the geostrophic current are solved analytically.

Mathematical model of infiltrative tumour growth taking into account transitions between two possible states of malignant cell is investigated. These transitions are considered to depend on oxygen level in a threshold manner: high oxygen concentration allows cell proliferation, while concentration below some critical value induces cell migration. Dependence of infiltrative tumour spreading rate on model parameters has been studied. It is demonstrated that if the level of tissue oxygenation is high, tumour spreading rate remains almost constant; otherwise the spreading rate decreases dramatically with oxygen depletion.

An approach to evaluation of a parametric portrait of integral equations of the theory of liquids in the RISM approximation was proposed. To obtain all associated solutions the continuation method was used. The equations reduced to a two-centered molecule model for symmetry reasons were deduced for molecular liquids. For molecular liquids, some equations were obtained which could be reduced, for symmetry reasons, to a two-center molecular model. To avoid critical points we changed the dependence of RISM-equations on reverse compressibility. The suggested method was used to perform numerical computations of methane reverse compressibility isotherms with three closures. No bifurcation of solutions was observed in the case of the partially linearized hypernetted chain closure. For other closures bifurcations of solutions were obtained and the model behavior nontypical for simple liquids was observed. In the case of Percus-Yevick closure nonphysical solutions were obtained at low temperature and density. Additional solution branch with a kink in the bifurcation point was obtained in the case of hypernetted chain closure at temperature above the critical point.

Numerical methods of obtaining collective and one-particle states were used for the quantum description of two-nuclear systems behavior at the initial stage of near-barrier heavy nuclei fusion. The collective exited states in such systems represent concordant oscillations of surfaces of spherical nuclei. The one-particle states of the external neutrons are similar to the states of valence electrons of diatomic molecules.

A two-dimensional system of excitable cells, describing by the FitzHugh-Nagumo model, has been used for a theoretical investigation of an action potential propagation (AP) in vascular plant tissues. It is shown that growth of electrical conductivity between cells increases the AP generation threshold and its propagation velocity in the homogeneous system, which has been formed by equal elements. The plant symplast has been
described by the heterogeneous system, including elements with low electrical conductivity, which simulate parenchyma cells, and elements with high electrical conductivity, which simulate sieve elements. Analysis of this system shows that the threshold of the AP generation is similar with this threshold in the homogeneous system
with low electrical conductivity; the velocity of the AP propagation is faster than one in this system.

A mathematical model for the evolution of microbial populations during prolonged cultivation in a chemostat has been constructed. This model generalizes the sequence of the well-known mathematical models of the evolution, in which such factors of the genetic variability were taken into account as chromosomal mutations, mutations in plasmid genes, the horizontal gene transfer, the plasmid loss due to cellular division and others. Liapunov’s function for the generic model of evolution is constructed. The existence proof of bounded, positive invariant and globally attracting set in the state space of the generic mathematical model for the evolution is presented because of the application of La-Salle’s theorem. The analytic description of this set is given. Numerical methods for estimate of the number of limit sets, its location and following investigation in the mathematical models for evolution are discussed.

The method of modelling of a compact bone tissue microstructure is presented. The modelling sample is considered as set of the structural elements containing reinforcing element – osteon and a matrix. The form of structural elements is defined by distances to next osteons and directions of next osteons arrangement. Calculation of the stress and strain state of the modelling sample is carried out at tension in program complex ANSYS. Results of calculation have shown, that haversian canals are stress concentrators.