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Features in the design of optimal recognition systems

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Abstract

Features that are inherent to recognition systems that lay claim to constituting an optimal design are considered. A maximal probability of correct recognition is characteristic of such systems. The degree of optimality of systems, the quality of a constructed classifier, or the dimension of the confidence interval may be established on the basis of these features.

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References

  1. Kapustiy, B.O., Rusyn, B.P., and Tayanov, V.A., Systemy rozpiznavannya obraziv z malymy bazamy danykh (Image Recognition Systems with Small Databases), L’viv: SPOLOM, 2006.

    Google Scholar 

  2. Kapustiy, B.O., Rusyn, B.P., and Tayanov, V.A., Parametric Synthesis of Recognition Algorithms with Differential Reliability Indicators, Tezy dop. Tret’oyi mizhnar. nauk.-tekhn. konf. z optoelektronnykh infomatsiynykh tekhnologiy “Fotonika-ODS-2005” (Proc. Third Intern. Scientific and Technical Conference on Optoelectronics Information Technologies (Fotonika-ODS-2005)), Vinnttsya, 2005, pp. 103–104.

  3. Kapustiy, B.E., Rusyn, B.P., and Tayanov, V.A., Parametric Synthesis of Recognition Systems, Materialy mezhdunarodnoy molodezhnoy nauch.-tekhn. konf. studentov, aspirantov i uchenykh “Molodezh’ i sovremennye problemy radiotekhniki i telekommuniicatsyy RT-2006” (Proc. Intern. Young Scientific and Technical Conference of Undergraduate and Graduate Students and Scientists “Youth and Modern Problems of Electronics and Telecommunications (RT-2006)”), Sevastopol’, 2006, p. 181.

  4. Kapustiy, B.O., Rusyn, B.P., and Tayanov, V.A., Parametrical Recognition Algorithm Synthesis Based on the Sequential Analysis, Proc. Intern. Conf. TCSET’2006;, “Modern Problems of Radio Engineering, Telecommunications and Computer Science”, Lviv-Slavsko, 2006, pp. 294–296.

  5. Kapustiy, B.E., Rusyn, B.P., and Tayanov, V.A., Optimization of Classifiers under Conditions of Small Samples, Avtom. Vychisl. Tekh., 2006, issue 5, pp. 25–32 [Autom. Control Comput. Sci., 2006, issue 5].

  6. Kapustiy, B.O., Rusyn, B.P., and Tayanov, V.A., Optimization of Classifiers in Attribute and Metric Spaces, Obroblennya signaliv i zobrazhen’ ta rozpiznavany-ya obraziv: Pratsi 8-yi Vseukr. mizhnar. konf. (Processing of Signals and Images: Proc. 8th All-Ukraine Intern. Conf.), Kyiv, 2006, p. 31–34.

  7. Tayanov, V.A., Optimization of Classifiers under Conditions of Small Samples, Mater. XIX vidkr. nauk.-tekhn. Konf. molodykh naukovtsiv i spetsialistiv “Diagnostychnisystemy” (Proc. 19th Research Conf. of Young Scientists and Specialists “Systems Diagnostics”), L’viv, 2005, pp. 367–370.

  8. Zhuravlev, Yu.I., Ryazonov, V.V., and Senk’ko, O.V., Raspoznavanie. Matematicheskie melody. Programmnye sistema. Prakticheskie primeneniya (Recognition. Mathematical Methods. Software Systems. Practical Applications), Moscow: Fazis, 2005.

    Google Scholar 

  9. Webb, A.R., Statistical Pattern Recognition, Chester (West Sussex, England): John Wiley & Sons, 2002.

    MATH  Google Scholar 

  10. Linnik, Yu.V., Statisticheskie zadachi s meshayushchimi parametrami (Statistical Problems with Interfering Parameters), Moscow: Nauka, 1966.

    Google Scholar 

  11. Tu, G. and Gonsales, R., Principles of Pattern Identification, Moskow: Mir, 1976.

    Google Scholar 

  12. Todd, K.M. and Wynn, C.S., Mathematical Methods and Algorithms for Signal Processing, Prentice-Hall, 2000.

  13. Weinstein, Eric W. Gauss’s Inequality / Math World-A Wolfram Web Resource.

  14. Hyvarinen, A., Karhunen, J., and Oja, E., Independent Component Analysis, New York: John Wiley & Sons, 2001.

    Google Scholar 

  15. Bronshtein, I.N. and Semendyaev, K.A., Spravochnik po matematike dlya inzhenerov i uchashchikh vuzov (Handbook on Mathematics for Engineers and Students at Technical Institutes), Moscow: Nauka, 1986.

    Google Scholar 

  16. Korolyuk, V.S., Portenko, N.I., Skorokhod, A.V., and Turbin, A.F., Spravochnik po teorii veroyatnostei i matematicheskoi statistike (Handbook on Probability Theory and Mathematical Statistics), Moscow: Nauka, 1985.

    Google Scholar 

  17. Kapustiy, B.O., Rusyn, B.P., and Tayanov, V.A., Peculiarities of Application of Statistical Detection Criteria for Problems of Pattern Recognition, J. Autom. Inform. Sci., 2005, vol. 37, no. 2, pp. 30–36.

    Article  Google Scholar 

  18. Gurov, S.I., Otsenka nadezhnosti klassifitsiruyushchikh algoritmov (Estimation of the Reliability of Classifying Algorithms), Moscow: Izd. Otd. F-ta VmiK MGU, 2003.

    Google Scholar 

  19. Vapnik, V.N., The Nature of Statistical Learning Theory, New York: Wiley, 2000.

    MATH  Google Scholar 

  20. Schlesinger, M.I. and Hlavac, V., Ten Lectures on Statistical and Structural Pattern Recognition (Computational Imaging and Vision), Springer, 2002.

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Authors and Affiliations

  1. L’vov Polytechnic National University, L’vov, Ukraine

    B. E. Kapustii

  2. Karpenko Institute of Physics and Mechanics, National Academy of Sciences of Ukraine, Ul. Nauchnaya 5, L’vov, 79601, Ukraine

    B. P. Rusyn & V. A. Tayanov

Authors
  1. B. E. Kapustii
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  2. B. P. Rusyn
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  3. V. A. Tayanov
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Corresponding author

Correspondence to V. A. Tayanov.

Additional information

Original Russian Text © B.E. Kapustii, B.P. Rusyn, V.A. Tayanov, 2008, published in Avtomatika i Vychislitel’naya Tekhnika, 2008, No. 2, pp. 15–23.

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Kapustii, B.E., Rusyn, B.P. & Tayanov, V.A. Features in the design of optimal recognition systems. Aut. Conrol Comp. Sci. 42, 64–70 (2008). https://doi.org/10.3103/S0146411608020028

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  • DOI: https://doi.org/10.3103/S0146411608020028

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