Issue 186, article 7


KVT, 2016, Issue 186, pp.78-94

UDС 615.47; 004.9


Vovk M.I.

International Research and Training Center for Information Technologies and Systems of National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

Introduction. Movement training is one of the main factors to mobilize person’s reserves at movement restoration.

The purpose of this article is to show the role of new bioinformatics technology and digital medical devices, original methods, programs and techniques of movement training of the limbs and fine motor hand, to restore motor and speech functions in patients after stroke.

Results. The bioinformatics technology TRENAR® for motor and speech rehabilitation is presented. The technology uses various programs (models) and methods for forced and voluntary movement training that are based on special   EMG signals processing and their transformation into informative visual and sound signals, that define movements. Structural – functional models of damaged motor area of the cortex reorganization aimed at motor control restoration according to movement training programs “Synthesis” (artificially synthesized programs of electric stimulation), “Donor” (programs are based on voluntary contractions of healthy muscles of a patient), “Biotraining” (Biofeedback method) are described. The technology is implemented in two electronic devices of digital medicine Trenar-01 and Trenar-02. New method and technology to restore speech on the basis of original techniques of fine motor hand training and technology TRENAR® are described. The results of clinical testing of technology in motor and speech restoration of patients after the stroke are presented.

Conclusion. The main benefits of the technology TRENAR® which lead to an increase in efficiency of motor and speech rehabilitation are as follows: advanced range of training programs, based on different methods, original techniques of fine motor hand training allows one to select individual approach to rehabilitation process.

Keywords: bioinformatics technology, digital medicine, electronic devices, programmed electric stimulation, biofeedback, rehabilitation, movement, hand, speech, stroke, individual approach.

Download full text (ru)!


1 Belova A.N., Prokopenko S.V. Neurorehabilitation. 3th ed. Moscow, 2010, 1288 p. (in Russian).

2 Aleev L., Vovk M., Gorbanev V. & others. “Mioton” in motor control. Kiev, 1980, 142 p. (in Russian).

3 Aleev L. S., Vovk M.I. Functional electrostimulation with myofeedback in movement rehabilitation. Proc. “5th International Muscle Symposium” (May 19-21, 2000, Viena, Austria). Viena, 2000, pp.69-70.

4 Gritsenko V.I., Kotova A. B., Vovk M. I. & others. Information technology in Biology and Medicine. Lecture course. Kiev, 2007, pp. 285-340 (in Ukrainian).

5 Vovk M.I. Bioinformatic technology of movements control as the direction of biological and medical cybernetics. Kibernetika i vycislitel’naa tehnika, 2013, No 174, pp. 56–70. (in Russian).

6 Gritsenko V.I., Vovk M.I. “TENAR” – innovational technology of movements restoring Materials of the International scientific – practical forum ” The Science and Business – a basis of development of economy ” . Dnepropetrovsk, 2012, pp.204-206. (in Russian).

7 Hunter P. Peckham, Kevin L. Kilgore, “Challenges and Opportunities in Restoring Function after Paralyses. IEEE Trans. Biomed. Eng.2013, Vol. 60, No .3, pp. 602-609.

8 Romanov S.P. Neurophysiological mechanisms of motor functions homeostasis / Doctor in Biology: specialty. 03.00.13. St. Petersburg, 1989, 443 p. (in Russian).

9 Anohin P.K. The Sketches on Physiology of Functional Systems. M.: Medicine, 1975, 447 p. (in Russian).

10 The method of Motor Control of a Person. Patent 41 795 Ukraine. 10.06.2009. (in Ukrainian).

11 Electrical stimulator. Patent. 32376 Ukraine: 12 .05. 2008. (in Ukrainian).

12 The Inventor’s Certificate on author’s product right 26 836 Ukraine. The Device for Electrical Stimulation with Biocontrol Trenar-01. The Technique for Using / M. Vovk, V. Ivanov, A. Shevchenko / 09.12.2008. (in Ukrainian).

13 Vovk M., Gorbanev V., Shevchenko A. The Inventor’s Certificate on author’s product right 37243 Ukraine. The Device for Electrical Stimulation with Biofeedback Trenar-02. The Technique for Using . 04.03.2011. (in Ukrainian).

14 Koltsova M.M. Motor activity and development of the child’s brain functions. Moscow: “Pedagogika”, 1973. 143 p. (in Russian).

15 Vovk M.I. , Galyan Ye. B. Restoring of motor component of speech based on muscle movement control. Theoretical grounding . Kibernetika i vycislitel’naa tehnika, 2012, Is. 167, pp.51-60. (in Russian).

16 16. The way to treat speech desorders. UA, A61N 1/36, no. 111388, 2016.(in Ukrainian).

17 Halverson H. M. The acquisition of skill in infancy. Journal of Genetic Psychology. 1933, Vol. 43, pp. 3-48.

18 Vovk M.I. , Galyan Ye. B. Organization of Intelligent Hand Movements Control to Restore Speech. Kibernetika i vycislitel’naa tehnika, 2016, Is. 184, pp.25-43. (in Russian).

19 Galyan Ye.B. Specialized software module of speech rehabilitation technology, architecture and functional interaction of its components. Control Systems and Machines, 2014, No 6, pp. 52-58. (in Russian).

20 Vovk M.I., Peleshok S.R., Galyan Ye.B. & others The method of assessment of motor and sensory speech disorders. Collected papers of scientific-information center “Knowledge” based on XI International correspondence scientific-practical conference: “The development of science in the XXI century” part 3. Kharkiv: collected papers. D, 2016, pp. 70-76. (in Russian).

Received 03.10.2016

Issue 186, article 6


KVT, 2016, Issue 186, pp.56-78

UDC 681.3.06.14


Fainzilberg L.S.

International Research and Training Center for Information Technologies and Systems of the National Academy of Sciences of Ukraine and Ministry of Education and Science of Ukraine, Kiev, Ukraine

Introduction. Recently, a new class of information technologies (IT) — intelligent IT is widespread which, unlike traditional, operate generalized concepts — images, and provide more complete information about the external environment. One of the tasks requiring the involvement of intelligent IT — analysis and interpretation of complex form signals with a locally-focused information.

The purpose of the article is — to formulate the basic properties of intelligent IT complex form signal processing, demonstrate the ability to implement these features on the example of the innovative method fasegraphy and outline prospects for further development of this technology.

Methods. Fasegraphy is a high IT which is processing different complex form signals of physical nature, which, basing on a chain of intelligent computational procedures, enables the transition from the observed signal with a locally-focused features (raw material for technology) to information which is focused on a particular user (technology product). The main task of the scientific method fasegraphy aims to detect general laws of indicated signals to identify and use in practice the most effective computational procedures that can ensure this transition.

Results. Basic properties of intelligent IT — adaptation, learning, generalization, invariance, forecasting, understanding, flexibility, interoperability, accessibility have been formulated. Analysis of computational procedures chain in fasegraphy method, that provide a transition from the actually observed signals to technology product, shows that the method has all of the above properties, and therefore fasegraphy can be referred to intelligent ITs. New results have been presented from fasegraphy usage in pediatric cardiology and outlined prospects for the development of this method in two ways — by increasing the reliability of decision making in single-channel ECG and realization of intelligent processing tasks of other signals with locally-focused features.

Conclusions. Fasegraphy intelligent capabilities are far from exhausted and can be used to solve actual scientific and applied problems not only in cardiology but also in other applications.

Keywords: fasegraphy, information technology, complex shape signals, electrocardiogram.

Download full text (ru)!


  1. Omelchenko V.O. Orthogonal expansions of random signals and fields. Кiev: UMKVO, 1991, 142 p. (in Ukrainian).
  2. Murashko V.V., Strutynsky A.V. Electrocardiography. Moscow, 1991, 288 p. (in Russian).
  3. Primin M.A., Nedajjvoda I.V., Vasilev V.E. New algorithms for magnitokardiosignal processing. Control systems and machines, 1998, № 2, pp.48–62. (in Russian).
  4. Ronkin М.А., Ivanov L.B. Rheography in clinical practice. Moscow: SMC MBN, 1997, 250 p. (in Russian).
  5. Piloian G.О. Introduction to Thermal Analysis. Moscow, 1964, 231 p. (in Russian).
  6. Gritsenko V.I., Fainzilberg L.S. FASEGRAPH® — information technology for the integrated assessment of the cardiovascular system state of the electrocardiogram phase portrait. Information technologies for the Physician, 2013, № 3, pp.52–63. (in Russian).
  7. Fainzilberg L.S. Computer diagnostics by phase portrait of electrocardiogram. Kiev, 2013, 191 p. (in Russian).
  8. Katerinchuk I.P., Borisenko N.B. Heart rate variability and autonomic dysfunction in patients with metabolic syndrome. Arrhythmology, 2012, № 3(3), pp. 6–13. (in Ukrainian).
  9. Pavlichencko P.P. The influence of the playing load on the functional status of professional football players. World of medicine and biology, 2015, № 1(48), pp. 49–54. (in Russian).
  10. Ozhegov vocabulary. Available at: URL:
  11. Fainzilberg L.S. Information technology for signal processing of complex shape. Theory and practice. Kiev, 2008, 333 p. (in Russian).
  12. Gritsenko V.I. Intellectualization of Information Technologies. Science & Technology. Kiev: V.M. Glushkov Institute of Cybernetics of NAS of Ukraine, 1992, pp. 4–9. (in Ukrainian).
  13. Hawkins D., Blakeslee S. On intelligence. Moscow, St. Petersburg, Kiev, 2007, 128 p. (in Russian).
  14. Preston J., Bishop M. Views Into the Chinese Room: New Essays on Searle and Artificial Intelligence. Oxford, 2002, 410 p.
  15. Fainzilberg L.S. Simulation models of generating artificial cardiograms in terms of internal and external disturbances. Journal of Qafgaz University Mаthеmаtics and Computer Science, 2012, № 34, pp. 92–104. (in Russian).
  16. Fainzilberg L.S., Glushauskene G.A. Narrow-band Rejection Filter for Suppression of Harmonic Concentrated Interference on the Basis of Discrete Fourier Transform. Journal of Automation and Information Sciences, 2009, Vol. 41, Iss. 8. pp. 55–70.
  17. Fainzilberg L.S. Adaptive smoothing of noise in information technology processing of physiological signals. Mathematical Machines and Systems, 2002, № 3, pp. 96–104. (in Russian).
  18. Zywienz C., Borovsky D., Goettsch G.& others Methodology of ECG Interpretation in the Hanover Program. Meth. Inf. Med, 1990, № 29, pp. 375.
  19. Gritsenko V.I., Fainzilberg L.S. Computer diagnostics using complex-form signals under conditions of internal and external disturbances. Reports of the National Academy of Sciences of Ukraine, 2013, № 12, pp. 36–44. (in Russian).
  20. L.L., Shtarck M.B. About ECG phase portrait. Avtometriya, 1993, № 2, pp. 51–54. (in Russian).
  21. Fainzilberg L.S. A method of personalized assessment of functional state of human cardiovascular system. UA Patent112325. 2016. Bul. 16. (in Ukrainian).
  22. Fainzilberg L.S. The Performance Evaluation of Information Technology FASEGRAPH® According to the Independent Studies. Control systems and machines, 2014, № 2, pp. 84–92. (in Russian).
  23. Maydannik V.G., Khaitovych N.V., Fainzilberg L.S. & others The symmetry of the T-wave on the electrocardiogram as a marker of cardiometabolic risk in schoolchildren. International Journal of Pediatrics, Obstetrics and Gynecology, 2013, Vol. 4, № 3, pp. 35–39. (in Russian).
  24. Morozik А.А., Fainzilberg L.S. Diagnostic value of electrocardiosignal combined analysis on phase plane and heart rate variability in children with diabetic cardiomyopathy. International Journal of Pediatrics, Obstetrics and Gynecology, 2015, Iss. 7, № 1, pp. 11– 17. (in Russian).
  25. Kondratiuk A.S., Garkaviy S.I., Korshun M.M. & others.Evaluation of primary school pupil’s functional state in physical education classes and swimming lessons dynamics. Hygiene of settlements, 2014, № 64, pp. 302–308. (in Ukrainian).
  26. Fainzilberg L.S., Orikhovska K.B., Vakhovskyi I.V. Assessment of chaotic fragments shape of the single-channel electrocardiogram. Kibernetika i vyčislitelʹnaâ tehnika, 2016, № 183, pp. 4–24. (in Russian).
  27. Fainzilberg L.S. Method of evaluating the adequacy of reaction to load UA Patent 103229. 2015. Bul. 23. (in Ukrainian).
  28. Fainzilberg L.S., Soroka Т.V. Development of telemedicine system for remote monitoring of heart activity based on fasegraphy method. East Europe Journal of Enterprise Technologies, 2015, № 6/9(78), pp. 37–46.
  29. Fainzilberg L.S. Method for person identification by electrocardiogram UA Patent 105273. 2014. Bul. 8. (in Ukrainian).

Received 27.09.16

Issue 186, article 5


KVT, 2016, Issue 186, pp.46-56

UDC 681.518


Melnikov S.V., Volkov A.E., Komar N.N., Voloshenyuk D.A.

International Research and Training Center for Information Technologies and Systems, Kyiv, Ukraine , , ,

Introduction. The problem of increasing network performance is very relevant. In practice, the actual speed of data transmission / receiving is significantly lower than the bit rate supported by used network technology. The actual wireless network bandwidth depends on the used technology, the number of subscribers in the network, length and quality of communication channels, electromagnetic interference, weather, network equipment, protocols and many other factors.

The purpose. The project is based on applied research in the field of high-speed cycles control systems for net-centric dynamic application processes with spatially-distributed interrelated functional components. Thus it provides functional and temporal combination of internal resources of net-centric distributed control systems with objects and technological processes on the basis of shared use of dynamics models working in an accelerated time scale into a single space-time net-centric complex.

Results. To solve the problem of determining the quality of the data transfer process in order to further control and manage this process, a method which is based on software that works with any standardized computing environment was developed. This method detects and evaluates the operating parameters of the wired Internet network before, during and after transmission of the information data packets provides analytical (numerical values of time delay of packet transmission, the percentage of lost data, signal quality, transmission speed and receive speed) and graphic parameters to control information transmission routes. This paper provides the results of computer simulation which are represent the network connection quality.

Conclusion. Development a method for determining the quality of information data transmission via a wireless connection, also as a creating programs for protection against unauthorized network access — are a perspective research objectives. Results of simulations confirm the appropriateness of using the given method of data transfer control in the terrestrial wired data transmission systems and the need to develop such technology for wireless connection.

Keywords: network-centric; control technology; communication; computer modeling; virtual model.

Download full text!


  1. A.A. Mizin Transmission of information via circuit-switched communications networks. M.: Communications, 1977, 328 p.
  2. S.V. Pavlova, Y.P. Bogachuk, S.V. Melnikov Simulation technology of distributed network of aircraft control. Kibernetika i vyčislitelʹnaâ tehnika, 2011, Vol. 163, pp. 45–53.
  3. Method of control of the route and determine the quality of the transfer of information data through a wired Internet network. Patent of Ukraine №04108, IPC (2013) G06N 7/00, stated 15/05/2014, Published 07/16/2014.
  4. V.P. Kharchenko, S.M. Kredentsar Networks and databases. NAU, Kiev, 2013, 328 p.
  5. 2013-2028 Global Air Navigation Plan. The capacity and effectiveness. International Civil Aviation Organization ICAO. Montreal, Canada, 2013, Vol. 4, 128 p.
  6. S.M. Pauk Aeronautical Telecommunication Networks. M.: Transport, 1986, 271 p.

Received 28.11.2016

Issue 186, article 4


KVT, 2016, Issue 186, pp.30-46

UDC 519.71


Gubarev V.F.

Space Research Institute NAS Ukraine and SSA Ukraine, Kiev, Ukraine

Introduction. Very significant for application model reduction problem of large-scale time-invariant system to more simple small order is considered and developed in the paper. Real and approximate models fitting is determined by norms which establish the difference between impulse response of these two models.

The purpose of the article is to propose a new approach of setting the model reduction problem and to develop methods based on variational principle of its solving.

Methods. It is proposed to set model reduction problem as optimization. For this initial state space model was transformed to equivalent description in form of input-output relation using analytical expression for impulse response. Such form allows to apply conception of fit between real system and its low-order approximation widely used in identification. Parameters of approximate model and its dimention are determined from optimization problem with different measure of fit writing as norm. Algorithms of numerical solving the optimization problems and needed for this data are considered in the paper. Besides the modified subspace method that permits to construct the observability matrix directly from output data using SVD factorization is proposed and described. Singular values of SVD-decomposition indicate as the best way to truncate full model.

Results. Some results dealing with mutual disposition of eigenvalues of real model and reduced one are demonstrated.

Conclusion. Developed methods may be used both for systems with scalar input and output and for multi-input and multi-output system as well. Results obtained by modelling show efficiency of all worked out methods.

Keywords: model reduction, approximation, optimization, model fit, state-space model.

Download full text (ru)!


1 Mischenko E.F., Rozov N.H. Differential equations with small parameter and relaxation oscillations. M.: Nauka. 1975, 248 p. (in Russian).

2 Antoulas A.C., Sorenson D.C., Gugercin S.A. A survey of model reduction methods for large-scale systems. Contemporary Mathematics. 2001, Vol. 280, pp. 193–219.

3 Reis T., Stykel T. A survey on model reduction of coupled systems. Model order Reduction. Theory, Research Aspects and Applications. 2008.

4 Gubarev V.F. Method of iterative identification of multivariable systems over inexact data. Part 1. Theoretical aspects. Journal of Automation and Information Sciences, 2006, No5,pp. 16–31 (in Russian).

5 Gubarev V.F. and Melnichuk S.V. Identification of multivariable systems using steady-state parameters. Journal of Automation and Information Sciences, 2012, No 5, pp. 26–42 (in Russian).

6 Rainer S., Price K. Differential evolution – a simple and efficient adaptive scheme for global optimization over continuous spaces. Journal of Global Optimization, 1997, No 11, pp. 341–359.

7 Golub G.H. and Van Loan Ch.F. Matrix Computations. Baltimore and London: John Hopkins University Press, 1999, 550 p.

8 Melnichuk S.V. Method of structural parametric multivariable systems identification using frequency characteristics. Kibernetika i vycislitel’naa tehnika, 2015, No 181, p. 66–79 (in Russian).


Received 15.09.16

Issue 186, article 3


KVT, 2016, Issue 186, pp.15-30

UDC 517.977


Chikrii A.A.

Glushkov Institute of Cybernetics NAS of Ukraine, Kiev, Ukraine

Introduction. Mathematical theory of control under conflict and uncertainty provides a wide range of fundamental methods to study controlled evolutionary processes of various nature. These are, first of all, the classic methods of L.S. Pontryagin and N.N. Krasovskii. This paper is closely related to the mentioned investigations. It is devoted to research of non-stationary game dynamic problems on the basis of the L.S. Pontryagin first direct method and the method of resolving functions.

The purpose of the paper is to derive sufficient conditions for the game termination for some guaranteed time in favor of the first player and to provide the control realizing this result.

Results. Here, in the development of the method of resolving functions general scheme, the upper and the lower resolving functions of two types are introduced in the form of selections of special set-valued mappings. This made it possible to deduce conditions for the game termination in the class of quasi- and stroboscopic strategies.

Conclusions. The in-depth analysis of properties of the set-valued mappings and their selections, around which measurable controls are chosen by virtue of the Filippov-Castaing theorem, is provided. A comparison of the guaranteed times of the above-mentioned methods is given.

Keywords: Conflict controlled processes, set — valued map, Pontryagin’s condition, Aumann’s integral, resolving function.

Download full text (ru)!


  1. Pontryagin L.S. Selected scientific papers. M.: Nauka, 1988, 576p. (in Russian)
  2. Krasovskii N.N. Game Problems on the Encounter of Motions, M.: Nauka, 1970. 420 p. (in Russian)
  3. Chikrii A.A. Conflict controlled processes. Boston; London; Dordrecht: Springer Science and Busines Media, 2013, 424 p.
  4. Chikrii A.A. An analytic method in dynamic games. Trudy Mat. Inst. RAN im. V.A. Steklova, 2010. Vol.271. pp. 76–92. (in Russian)
  5. Aubin J.-P., Frankowska H. Set — valued analysis. Boston; Basel; Berlin: Birkhauser, 1990, 461 p.
  6. Hajek O. Pursuit games. New York: Academic Press, 1975, Vol. 12, 266 p.
  7. Lappo — Danilevsky I.A. Application of the matrix functions to the theory of systems of ordinary differential equations. M.: SPHTTL, 1957, 235 p. (in Russian)
  8. Pschenichnyi B.N Convex analysis and extremal problems. M.: Nauka, 1980, 320 p. (in Russian)

Received 13.09.2016

Issue 186, article 2


KVT, 2016, Issue 186, pp.5-15

UDС 519.72


Anisimov A.V.

Taras Shevchenko National University of Kiev, Ukraine

Introduction. Two-level system of encoding integers by linear forms aPn + bQn, where Pn and Qn are linear recurrent sequences. These sequences are defined by factoring quadratic irrationalities into continued fractions. Firstly, a number x is represented as a form x = aAn + bBn, where An / Bn is a convergent to some fixed quadratic irrationality. At the second stage the triple (a, b, n) is encoded by a maximal linear form of another linear recurrent sequence (a, b, n) -> cPn + dPn+1. The sequences An, Bn, Pn are considered as hidden symmetric keys given by coefficients of corresponding quadratic irrationalities. Properties of such encodings are established.

The purpose of the article is to develop and study a nondeterministic system of cryptographic integer encoding by means of linear recurrent sequences.

Methods. We used methods of continued fractions, properties of linear forms, and bijective encoding of natural numbers.

Results. We proved as a theorem that such a system of encoding is absolutely resistant to passive crypto-attacks. With some further additions it is also resistant to stronger types of attacks.

Conclusion. The proposed system of integer encoding is easy to construct, and it has some proven properties that allows using it as a primitive basic procedure for light weighted cryptography.

Keywords: Linear forms, continued fractions, nondeterministic cryptography.

Download full text (ru)!


1 Bellare, M., Rogaway,P.: Optimal Asymetric Encryption In: De Santis, A. (ed) Advances of Cryptology: Proceedings of EURO-CRYPT ’94, LNCS, 1995. vol. 950, pp. 92-111.

2 Anisimov A. V. Data Coding by Linear Forms of Numerical Sequences. Cybernetics and Systems Analysis, 2003, No 1, pp. 3-15.

3 Anisimov A. V. Integer representation in the mixed base (2,3). Cybernetics and Systems Analysis, 2009, No 4, pp. 3-18

4 Anisimov A. V. Two-base numeration systems. Cybernetics and Systems Analysis, 2013, No 4, pp. 1-14.

5 Anisimov A. V. Prefix Encoding by Means of the (2,3)-Representation of Numbers. IEEE Transactions on Information Theory, 2013, vol. 59, No 4, pp. 2359-2374.

6 Anisimov A. V. Zavadskyi I. A. Robust Prefix Encoding Using Lower (2,3) Number Representation. Cybernetics and Systems Analysis, 2014, No 2, pp.1-15.

Received 03.10.2016