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Optical systems with two-dimensional feedback demonstrate wide possibilities for studying the nucleation and development processes of dissipative structures. Feedback allows to influence the dynamics of the optical system by controlling the transformation of spatial variables performed by prisms, lenses, dynamic holograms and other devices. A nonlinear interferometer with a mirror image of a field in two-dimensional feedback is one of the simplest optical systems in which is realized the nonlocal nature of light fields.

A mathematical model of optical systems with two-dimensional feedback is a nonlinear parabolic equation with rotation transformation of a spatial variable and periodicity conditions on a circle. Such problems are investigated: bifurcation of the traveling wave type stationary structures, how the form of the solution changes as the diffusion coefficient decreases, dynamics of the solution’s stability when the bifurcation parameter leaves the critical value. For the first time as a parameter bifurcation was taken of diffusion coefficient.

The method of central manifolds and the Galerkin’s method are used in this paper. The method of central manifolds and the Galerkin’s method are used in this paper. The method of central manifolds allows to prove a theorem on the existence and form of the traveling wave type solution neighborhood of the bifurcation value. The first traveling wave born as a result of the Andronov –Hopf bifurcation in the transition of the bifurcation parameter through the сritical value. According to the central manifold theorem, the first traveling wave is born orbitally stable.

Since the above theorem gives the opportunity to explore solutions are born only in the vicinity of the critical values of the bifurcation parameter, the decision to study the dynamics of traveling waves of change during the withdrawal of the bifurcation parameter in the supercritical region, the formalism of the Galerkin method was used. In accordance with the method of the central manifold is made Galerkin’s approximation of the problem solution. As the bifurcation parameter decreases and its transition through the critical value, the zero solution of the problem loses stability in an oscillatory manner. As a result, a periodic solution of the traveling wave type branches off from the zero solution. This wave is born orbitally stable. With further reduction of the parameter and its passage through the next critical value from the zero solution, the second solution of the traveling wave type is produced as a result of the Andronov –Hopf bifurcation. This wave is born unstable with an instability index of two.

Numerical calculations have shown that the application of the Galerkin’s method leads to correct results. The results obtained are in good agreement with the results obtained by other authors and can be used to establish experiments on the study of phenomena in optical systems with feedback.

Correct modeling of complex dynamics of urban transportation flows requires the collection of large volumes of empirical data to specify types of the modes and their identification. At the same time, setting a large number of observation posts is expensive and technically not always feasible. All this results in insufficient factographic support for the traffic control systems as well as for urban planners with the obvious consequences for the quality of their decisions. As one of the means to provide large-scale data collection at least for the qualitative situation analysis, the wide-area video cameras are used in different situation centers. There they are analyzed by human operators who are responsible for observation and control. Some video cameras provided their videos for common access, which makes them a valuable resource for transportation studies. However, there are significant problems with getting qualitative data from such cameras, which relate to the theory and practice of image processing. This study is devoted to the practical application of certain mainstream neuro-networking technologies for the estimation of essential characteristics of actual transportation flows. The problems arising in processing these data are analyzed, and their solutions are suggested. The convolution neural networks are used for tracking, and the methods for obtaining basic parameters of transportation flows from these observations are studied. The simplified neural networks are used for the preparation of training sets for the deep learning neural network YOLOv4 which is later used for the estimation of speed and density of automobile flows.

The work is devoted to the structural analysis of complex technical systems. Mechanical structures are considered, the properties of which affect the behavior of products during assembly, repair and operation. The main source of data on parts and mechanical connections between them is a hypergraph. This model formalizes the multidimensional basing relation. The hypergraph correctly describes the connectivity and mutual coordination of parts, which is achieved during the assembly of the product. When developing complex products in CAD systems, an engineer often makes serious design mistakes: overbasing of parts and non-sequential assembly operations. Effective ways of identifying these structural defects have been proposed. It is shown that the property of independent assembly can be represented as a closure operator whose domain is the boolean of the set of product parts. The images of this operator are connected and coordinated subsets of parts that can be assembled independently. A lattice model is described, which is the state space of the product during assembly, disassembly and decomposition into assembly units. The lattice model serves as a source of various structural information about the project. Numerical estimates of the cardinality of the set of admissible alternatives in the problems of choosing an assembly sequence and decomposition into assembly units are proposed. For many technical operations (for example, control, testing, etc.), it is necessary to mount all the operand parts in one assembly unit. A simple formalization of the technical conditions requiring the inclusion (exclusion) of parts in the assembly unit (from the assembly unit) has been developed. A theorem that gives an mathematical description of product decomposition into assembly units in exact lattice terms is given. A method for numerical evaluation of the robustness of the mechanical structure of a complex technical system is proposed.

In various applications, i. e., astronomical imaging, electron microscopy, and tomography, images are often damaged by Poisson noise. At the same time, the thermal motion leads to Gaussian noise. Therefore, in such applications, the image is usually corrupted by mixed Poisson – Gaussian noise.

In this paper, we propose a novel method for recovering images corrupted by mixed Poisson – Gaussian noise. In the proposed method, we develop a total variation-based model connected with the nonconvex function and the total generalized variation regularization, which overcomes the staircase artifacts and maintains neat edges.

Numerically, we employ the primal-dual method combined with the classical iteratively reweighted $l_1$ algorithm to solve our minimization problem. Experimental results are provided to demonstrate the superiority of our proposed model and algorithm for mixed Poisson – Gaussian removal to state-of-the-art numerical methods.

The work analyzes known classes of convolutional neural network models and studies selected from them promising models for detecting flying objects in images. Object detection here refers to the detection, localization in space and classification of flying objects. The work conducts a comprehensive study of selected promising convolutional neural network models in order to identify the most effective ones from them for creating mobile real-time computer vision systems. It is shown that the most suitable models for detecting flying objects in images, taking into account the formulated requirements for mobile real-time computer vision systems, are models of the YOLO family, and five models from this family should be considered: YOLOv4, YOLOv4-Tiny, YOLOv4-CSP, YOLOv7 and YOLOv7-Tiny. An appropriate dataset has been developed for training, validation and comprehensive research of these models. Each labeled image of the dataset includes from one to several flying objects of four classes: “bird”, “aircraft-type unmanned aerial vehicle”, “helicopter-type unmanned aerial vehicle”, and “unknown object” (objects in airspace not included in the first three classes). Research has shown that all convolutional neural network models exceed the specified threshold value by the speed of detecting objects in the image, however, only the YOLOv4-CSP and YOLOv7 models partially satisfy the requirements of the accuracy of detection of flying objects. It was shown that most difficult object class to detect is the “bird” class. At the same time, it was revealed that the most effective model is YOLOv7, the YOLOv4-CSP model is in second place. Both models are recommended for use as part of a mobile real-time computer vision system with condition of additional training of these models on increased number of images with objects of the “bird” class so that they satisfy the requirement for the accuracy of detecting flying objects of each four classes.

In our work we present generalization of well-known approach for construction of invariant feature vectors of images in computer vision applications. Basic feature of the suggested algorithm is replacement of commonly used Gaussian filter by convolution of image function with Green’s function of evolution operator, which inherits symmetries of this operator. The use of general filtration allows to obtain additional characteristics of invariant feature vectors.

The question on improvement of quality of images obtained in a tomography problem is considered. The problem consists in finding of boundaries of inhomogeneities (inclusions) in a continuous medium by results of X-ray radiography of this medium. A nonlinear integral transformation of a special kind is proposed which allows to improve quality of images obtained earlier at a set of papers. The method is realized numerically by the use of computer modelling. Some calculations are carried out with use of data for concrete materials. The results obtained are presented by drawings and graphic images.

The article presents the intermediate results of the development of a control system for a remotely piloted agricultural aircraft (RPAA). The concept of using an automated complex for performing aerochemical work (ACW) designed for processing fields, water areas, forests with the purpose of protection from pests of plants, fertilization is developed. The basic component of the complex is a manned agricultural aircraft MV-500 developed by LLC “Firm “MVEN” (Kazan). The use of the aircraft in unmanned mode will provide an increase in the productivity of the aircraft, will increase the payload.

The article defines the composition of the complex for automation of ACW: aircraft, ground control center, onboard equipment for automated control of the aircraft and the formation of a map of the heights of the section being processed, and the satellite precise positioning system necessary to automate the control of the aircraft. The aircraft is equipped with an automated control system that provides remote control of take-off and landing and automatic control of the flight trajectory at extremely low altitude when performing ACW and performing spatial turns at the boundaries of the treated areas. It is proposed to take off, landing, dropping an aircraft into the ACW exercise area by means of a pilot operator from a ground control station. The ground control point should provide reception and display on the operator's screen of flight information and several types from the aircraft. The operator can control alternately several aircraft during these phases of flight with the help of ground control authorities. In the future, it is planned to automate these stages of flight, leaving behind the pilot-operator control functions and remote control capabilities in special cases. For the navigation of the aircraft, when performing ACW on board, RTK (Real Time Kinematic) equipment is installed, providing a measurement with centimeter accuracy of coordinates and aircraft heights relative to the base station installed in the ground control station. Before the implementation of ACW, a three-dimensional digital map of the processed area is built by adding existing cadastral maps with measurements of the elevations of the section carried out with the help of on-board radio and optical altimeters of the same aircraft.

To date, the following system components have been manufactured and tested: a remotely controlled model of the MV-500 aircraft at a scale of 1:5, a satellite positioning system; system for obtaining images and telemetry information from the board model; autopilot; methods of obtaining three-dimensional digital maps of sections and planning flight trajectories for ACW.

The general formalization of visualization models in cellular automata (CA) scope is presented, their classification is examined. It also describes possible approaches to the sound scales generation. We consider special cases of visualization manners for CA of various dimensions. By a simple 3D CA example the features of nanoscale systems imaging are indicated.

To determine movements of infrastructure objects on Earth surface, SAR interferometry is used. The method is based on obtaining a series of detailed satellite images of the same Earth surface area at different times. Each image consists of the amplitude and phase components. To determine terrain movements the change of the phase component is used. A method of persistent scatterers detection and estimation of relative shift of objects corresponding to persistent scatterers is suggested.