Article 1116

Title of the article

A FAST SYMMETRIZATION ALGORITHM FOR CORRELATIONS OF BIOMETRIC DATA OF HIGH DIMENSION 

Authors

Volchikhin Vladimir Ivanovich, Doctor of engineering sciences, professor, President of Penza State University (40 Krasnaya street, Penza, Russia), cnit@pnzgu.ru
Akhmetov Berik Bakhytzhanovich, Candidate of engineering sciences, vice-president of Hodja Ahmet Yassawi International Kazakh-Turkish University (B. Sattarkhanova avenue, Turkestan, Kazakhstan), berik.akhmetov@ayu.edu.kz
Ivanov Aleksandr Ivanovich, Doctor of engineering sciences, associate professor, head of the laboratory of biometric and neural network technologies, Penza Research Institute of Electrical Engineering (9 Sovetskaya street, Penza, Russia), ivan@pniei.penza.ru

Index UDK

519.7; 519.66; 57.087.1, 612.087.1

Abstract

Background. The aim is to quickly calculate the correlation coefficients equal to the biometric data that are equivalent to conventional asymmetric correlation matrices of high dimension.
Materials and methods. It is shown that, similarly to Voltaire kernel symmetrization at identification of nonlinear dynamic objects in the related problem of biometric identification there can be used similar constructions that simplify calculations.
Results and conclusions. It is proved that the transition from conventional correlation matrices to matrices of equal correlation requires small test samples. The dimension of the correlation symmetrization problem to be solved does not affect the size of the required sample examples of a biometric image of "Friend". The computational complexity of the procedure of correlation symmetrization is less than the computational complexity of the complete coefficient matrix of pair correlations.

Key words

Volterra symmetric kernel, identification of nonlinear dynamic objects, correlation symmetrization, biometric identification

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References

1. Eykkhoff P. Osnovy identifikatsii sistem upravleniya [Foundations of control system identification]. Moscow: Mir, 1975, 517 p.
2. Marmarelis P., Marmarelis V. Analiz fiziologicheskikh sistem. Metod belogo shuma [Physiological system analysis. The white noise method]. Moscow: Mir, 1981, 480 p.
3. Ivanov A. I. Izmeritel'naya tekhnika [Measuring technology]. 1995, no. 10, pp. 13–15.
4. Ivanov A. I. Avtomatika i telemekhanika [Automatics and remote control]. 1997, no. 11, pp. 21–32.
5. Ivanov A. I. Upravlyayushchie sistemy i mashiny [Control systems and machinery]. 1999, no. 2, pp. 16–21.
6. Monrose F., Reiter M., Li Q., Wetzel S. Cryptographic key generation from voice. In Proc. IEEE Symp. on Security and Privacy, 2001.
7. Ramírez-Ruiz J., Pfeiffer C., Nolazco-Flores J. Advances in Artificial Intelligence – IBERAMIA-SBIA 2006 (LNCS 4140). 2006, pp. 178–187.
8. Hao F., Anderson Ross and Daugman John Crypto with Biometrics Effectively. IEEE TRANSACTIONS ON COMPUTERS. 2006, Sept., vol. 55, no. 9.
9. Volchikhin V. I., Ivanov A. I., Funtikov V. A. Bystrye algoritmy obucheniya neyrosetevykh mekhanizmov biometriko-kriptograficheskoy zashchity informatsii: monogr. [Fast algorithms for training neural-network mechanisms of biometric-cryptographic data protection: monograph]. Penza: Izd-vo PGU, 2005, 273 p.
10. Akhmetov B. S., Ivanov A. I., Funtikov V. A., Bezyaev A. V., Malygina E. A. Tekhnologiya ispol'zovaniya bol'shikh neyronnykh setey dlya preobrazovaniya nechetkikh biometricheskikh dannykh v kod klyucha dostupa: monogr. [Technology of large neural networks usage for fuzzy biometric data conversion to access key codes:monograph]. Kazakhstan, Almaty: LEM, 2014, 144 p.
11. Shalygin A. S., Palagin Yu. I. Prikladnye metody statisticheskogo modelirovaniya [Applied methods of statistical modeling]. Leningrad: Mashinostroenie, 1986, 320 p.
12. Akhmetov B. S., Nadeev D. N., Funtikov V. A., Ivanov A. I., Malygin A. Yu. Otsenka riskov vysokonadezhnoy biometrii: monogr. [Risk estimation in highly reliable biometrics: monograph]. Almaty: Iz-vo KazNTU im. K. I. Satpaeva, 2014, 108 p.

 

Дата создания: 01.07.2016 08:56
Дата обновления: 07.02.2017 08:22