# Optoelectronics, Instrumentation and Data Processing (v.44, #3)

A wire model of a spatial group point object by Y. A. Furman; K. B. Ryabinin; M. I. Krasilnikov

*(189-199)*. Obtaining an analytical model of a spatial group point object is considered in terms of quaternion analysis. The point ordering procedure consists in numbering vertices of a convex polyhedron associated with the object. The wire model is a spatial polygonal line passing through all object points without brunching.

The disorder problem for stochastic jump processes by G. I. Salov

*(200-210)*. A Bayes formulation for the problem of rapid detecting appeared disorders in the probability characteristics of the observed stochastic jump process with values in a sufficiently general phase space is presented. It is supposed that the time of disorder appearance does not depend on the evolution of the observed process and coincides with the moment of one of the process jumps. Recurrent equations for a posteriori disorder probability are obtained. The lower bound for the optimal moment of alarming the happened disorder for minimizing the sum of false alarm probability (without disorder) and the mean time of alarm delay is found.

Intellectual data analysis based on a rival similarity function by N. G. Zagoruiko

*(211-217)*. A uniform approach to constructing intellectual data analysis, or data mining is proposed. The approach is based on using a rival similarity function (FRiS function) representing the way of human estimation of similarity and dissimilarity. A brief description of data mining methods based on this approach is presented. Examples of solving model and real problems by these methods are illustrated.

Increasing the sine-cosine transformation accuracy in signal approximation and interpolation by V. M. Efimov; A. L. Reznik; Yu. V. Bondarenko

*(218-227)*. Sine-cosine transformations on the interval −0.5

*T*≤*t*≤ 0.5*T*, which are equivalent to a cosine transformation on the interval 0 ≤*t*≤*T*, are considered. Relationships for the error variance of signal reconstruction are obtained. Depending on the a priori information on the signal, the relationships make it possible to choose for its representation the most suitable orthogonal expansion. A stationary random signal model is used for comparing the expansion with a conventional sine-cosine transformation. Equivalent-time sampling and real-time digital oscillography interpolation by V. N. Vyukhin

*(228-231)*. Two methods for increasing the sampling rate in digital oscilloscopes are analyzed. The equivalent-time sampling is carried out via measuring and accumulating a series of oscillograms with a random phase and leads to nonuniform sampling. As a result, for few accumulations, the output noise level increases and the effective number of bits decreases. Interpolation in digital oscilloscopes is performed by sin

*x/x*functions and its errors are determined by the length of the interpolating FIR filter. A table for choosing the filter length, depending on the interpolation coefficient and the normalized band of the reconstruction filter is presented. Obtaining a high interpolation coefficient requires considerable computational power. Applying digital filtering based on a modified Capon approach to frequency-shift keyed signal demodulation by A. A. Loginov; O. A. Morozov; E. A. Soldatov; S. L. Khmelev

*(232-237)*. An algorithm for digital filtering based on the Capon approach for frequency-shift keyed signal demodulation is proposed. The filter coefficients correspond to an information-optimal solution to the problem of minimizing the output linear filter dispersion. It is shown that the method is efficient in the conditions of additive noises and inexact knowledge of the central signal frequency spectrum. The algorithm can be implemented on a programmable logic in real time.

Analysis of nonparametric pattern recognition algorithms under incomplete data by A. V. Lapko; V. A. Lapko

*(238-244)*. The nonparametric pattern recognition algorithms are investigated under incomplete data in the training sample. Requirements on the incomplete data filling methods are formulated by analyzing conditions of their asymptotic convergence.

Determining the object orientation in a 3D space by V. V. Trushkov; V. M. Khachumov

*(245-248)*. A method for determining an object orientation by a set of positions of its points located on faces of a 3D model or on surfaces is considered. An orthogonal position line algorithm is designed for measuring orientation angles and normalizing an object for subsequent control actions. Determining the orientation of a 3D object represented by a set of points on a cone surface is illustrated.

A rotation, translation, and scaling invariant Fourier transform of 3D image function by S. N. Chukanov

*(249-255)*. A rotation, translation, and scaling invariant Fourier transform of a 3D image function is proposed. The transform is based on expanding into a series of spherical functions.

Computer designing photometric pictures of diffusely-mirror objects by E. F. Ivankin; E. V. Peteshchenkov; V. A. Ponkin

*(256-263)*. The developed method for computer designing physically accurate pictures of irregular objects having optically coupled surfaces with diffuse, mirror, and diffusely-mirror reflections is based on solving generalized equations of theoretical photometry. The method is approved by results of mathematical simulation. Applicability of the method for designing pictures of a wider class of objects with diffusely-guided surface reflection is shown.

Measuring the deformity of dentofacial bone tissues using a speckle correlation method by Yu. N. Kulchin; O. B. Vitrick; A. D. Lantsov; V. A. Vorobyev; Yu. N. Moskvin

*(264-268)*. A noninvasive method for investigating the deformity of dentofacial bone tissues is proposed. The method is based on speckle field correlation analysis. The optimal conditions for the method are found. It is shown that the threshold sensitivity of the method may reach 10 μm.

A multiplicative model of plants’ season power consumption by R. R. Akhmetyanov; L. A. Delegodina; N. P. Kopylova; B. N. Lutsenko; G. M. Sobstel; G. P. Cheido

*(269-278)*. A system of transformations of the initial process with nonstationary season variations is considered. The process is described by an autoregressive multiplicative model and an integrated moving average for further forecasting. The transformations are completed by reducing the initial process to a stationary form to realize model identification and forecast the process.

Development of an automatic process control system for the Severomuiskii tunnel by B. N. Pishchik; L. A. Vorontsova; P. V. Iosifov; V. D. Neskorodev; V. V. Okol’nishnikov; T. M. Osokina; A. I. Fedorov; D. V. Chernakov

*(279-284)*. Implementation of an automatic process control system for the Severomuiskii tunnel is presented. Its subsystems are considered, which can be used for design of other similar control systems.