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An approach to processing images of three-dimensional objects which does not require knowledge of the ordering of the samples specifying the coordinates of points on the object surface is considered. The approach is based on obtaining a secondary analytical description of an object in the form of a polynomial function of a hypercomplex variable that projects samples of the object surface onto a sphere. It is shown that the method allows one to estimate scaling and rotation parameters and to recognize three-dimensional objects from polynomial coefficients. The performance of the proposed algorithms was estimated in experiments using images of real objects and mathematical models.

A method of synthesis of two-level non-parametric pattern recognition systems based on the principles of decomposition of learning samples in terms of their volume and on using the technology of parallel computations is proposed. The properties of these systems are analyzed on the basis of computational experiments performed.

A new approach to analyzing the data obtained by tracking biological objects in studying the motion activity is considered. The approach is based on a proposed mathematical model of motion of a biological object. The object behavior observed during the experiment can be described in the form of model parameters. A numerical experiment with model data is performed, which shows that the estimates predicted by the proposed method ensure a smaller root-mean-square deviation of the object state classification than other available methods.

A detailed review of the best-known methods for estimating fractal dimension (FD) is given, and their accuracy and computational complexity are demonstrated by estimating the FD of model images with a high degree of self-similarity. A new algorithm for estimating FD by linear transformations is proposed which gives much lower error without significantly increasing the computational complexity.

One possible approach of controlling laser systems based on galvanometric scanners for precision micromachining of continuously moving materials is considered. A variant of implementation of the system with sensors of relative displacements of the material and real-time correction algorithms is demonstrated, which ensures the micromachining velocity close to the maximum possible value for these scanners. Experimental results of micromachining of polymer tapes are given.

Specific features of operation of an autofocus in a CLWS-300IAE circular laser writing system are considered. The influence of the focus error on the process of direct laser writing of diffraction structures is considered. A digital adaptive controller for the system of autofocus control is described and studied in experiments. Algorithms of controller operation, a technique for its tuning, and experimental results are described.

Design principles of silicon multiplexers for linear and matrix infrared (IR) focal plane arrays (FPAs) are considered. Silicon multiplexers intended for operation with multielement mercury-cadmium-tellurium (MCT) photodiode detectors, with multielement photoresistor detectors based on multilayer structures with quantum wells, and with other types of photodetectors sensitive to radiation in the IR ranges from 3 to 5 and from 8 to 16 µm, are discussed. The type and size range of the multiplexers includes 19 models that differ in frame sizes, input circuits, charge capacity, and cell pitch. Around the designed multiplexers, hybrid and monolithic FPAs of various formats for medium and far IR ranges with a rather high temperature resolution (< 0.02 K) have been developed.

This paper considers the state and prospects for studies of the central problem of the theory and practice of automatic control-the problem of controller synthesis for systems with nonlinear plants. A crucial factor in the performance of controllers for nonlinear plants is the use of deep feedback for derivatives of the output variable, which provides localization of disturbances in fast subprocesses (against the background of the main processes) and allows the generation of the required dynamic properties

The degeneration property of dynamic multivariable control systems is considered. In this work, by degeneration for a multivariable systems is meant primarily a decrease and even a loss of its operating capacity. A technique of quantitative assessment of the tendency of multivariable control systems to degeneration was developed using a singular decomposition of criteria matrices formed on the basis of the matrix formalism of Faddeev-Leverrier algorithm, Gramian representation, matrix coefficient of the expansion of the system output vector in the derivatives of the control input vector, and with the use of the matrix formalism of Sylvester's and Lyapunov's equations.

Experimenting with large-scale, multi-agent software systems yields insight into factors that determine the capability of complex systems to operate at the edge of chaos without disintegrating. The research results are generalised and applied to the diagnosis of the failure of the global financial system.