Digital pulse neuron model for processing of wave accelerometer sensor signals

V.N. Bondarev, T.L Smetanina

Federal State Educational Institution of Higher Education «Sevastopol State University»

Russian Federation, Universitetskaya St.. 33

E-mail: bondarev@sevsu.ru,  fampoa@gmail.com

DOI: 10.33075/2220-5861-2017-2-16-23

UDC 621.372.54.037

Abstract:

   It is considered the problem of double integration of wave accelerometer sensor signals. The method of adaptive modeling using pulse neural network is proposed for the problem decision. Formulas of digital model of pulse neuron and also generalized and specialized learning rules are derived. Results of computer simulation are presented.

Keywords: pulse neural network, wave accelerometer sensor, estimation of wave parameters, double integration, learning rule.

Full text in PDF (RUS)

LIST OF REFERENCES

  1. Matveev V.V., Pogoreloe M.G. Sistema izmerenija vertikal’noj kachki volnomernogo buja. Izvestija TulGU. Tehnicheskie nauki. 2014. Vol. 9. No. 2. pp. 267-275.
  2. Grjazin D.G., Belova O.O. Inercial’nye metody izmerenija parametrov morskogo volnenija. Izvestija TulGU. Tehnicheskie nauki. 2016. Vol. 10. pp. 111-118.
  3. Bondarev V.N. Ustrojstvo dlja opredelenija srednej vysoty voln: a.s. 821918 SSSR. V.N. Bondarev, A.A. Kljucharev, G.A. Tihonov; zajavl. 15.06.79 2781304/18-10; opubl. 15.04.81, Bjul. No 14.
  4. Kozlov M.V., Matushevskij G.V., Trubkin I.P. Sposob opredelenija para-metrov vetrovyh voln na avtomaticheskih bujkovyh stancijah. Okeanologija. 1977. No 5. pp. 21-23.
  5. Bondarev V.N. Adaptivnoe chastotno-impul’snoe modelirovanie v zadachah cifrovoj obrabotki signalov.Vestnik SevGTU. Ser. Informatika, jelektronika, svjaz’: sb. nauch. tr. 1999. Vol. 18. pp. 46-51.
  6. Bondarev V.N., Smetanina T.I. Adaptivnyj sintez cifrovogo fil’tra dlja akselerometricheskogo volnografa. Sistemy kontrolja okruzhajushhej sredy. Sevastopol’: IPTS. 2015. Vol. 2 (22). pp. 25-28.
  7. Maass W. Paradigms for computing with spiking neurons. Models of Neural Networks. Early Vision and Attention; eds. J.L. van Hemmen. J.D. Cowan, E. Domany. New York: Springer, 2002. Vol. 4. pp. 373-402.
  8. Ponulak F., Kasinski A. Introduction to Spiking Neural Networks: Information processing, learning and applications. Acta Neurobiol Exp. 2011. Vol. 71 (4). pp. 409^33.
  9. Gelig A.X. Dinamika impul’snyh sistem i nejronnyh setej. JI.: Izd-vo LGU, 1982. 192 p.
  10. Bondarev V.N. On system identification using pulse-frequency modulated signals. Eindhoven: EUT, 1988. EUT Report 88-E-195. 82 p.
  11. Wei D., Harris J.G. Signal reconstruction from spiking neuron models. Proceedings of the 2004 International Sym-posium on Circuits and Systems. IEEE Press, 2004. Vol. 5. pp. 353-356.
  12. Bondarev B.H., Smetanina T.N. Formal’naja model’ impul’snogo nejrona dlja obrabotki signalov. Robototehnika i iskusstvennyj intellekt: materialy VI Vserossijskoj nauchno- tehnicheskoj konferencii. Krasnojarsk: Centr informacii CNI «Monografija», 2014. pp. 170-175.
  13. Bondarev V.N., Smetanina T.I. Adaptivnyj metod opredelenija kojefficientov chastotno-impul’snyh cifrovyh nerekursivnyh fil’trov. Informacionnye tehnologii i upravlenie. 2015. Vol. 1. No 1. pp. 41^17.
  14. Bondarev V.N. Primenenie cifrovoj modeli impul’snogo nejrona dlja adaptivnoj fil’tracii signalov. Nejroinformatika-2015 XV11 Vserossijskaja nauchno-tehnicheskaja konferencija s mezhdunar. uchastiem: sbornik nauchnyh trudov v 3-h ch.; otv. red. A.G. Trofimov. Moskwa: NIJaU MIFI, 2015. No. 2. pp. 169-177.
  15. Bondarev V.N. Impul’snye nejronnye seti i ih primenenie pri obrabotke signalov i izobrazhenij. Perspektivnye napravlenija razvitija otechestvennyh informacionnyh tehnologij: materialy II mezhregional’noj nauchno-prakticheskoj konferencii. Sevastopol’skij gosudarstvennyj universitet; nauch. red. B.V. Sokolov. 2016. pp. 111-112.
  16. Bondarev V.N. Pravila obuchenija impul’snogo nejrona dlja adaptivnoj obrabotki signalov. Nejroinformatika-2016 XVIII Mezhdunarodnaja nauchno- tehnicheskaja konferencija: sbornik nauchnyh trudov v 3-h ch. Moskwa: NIJaU MIFI, 2016. Vol. 2. pp. 192-202.
  17. Bondarev V. Vector-Matrix Models of Pulse Neuron for Digital Signal Processing. Advances in Neural Networks – ISNN 2016. Lecture Notes in Computer Science. Springer-Verlag GmbH ,2016. Vol. 9719. pp. 647-656. DOI: 10.1007/978-3- 319—40663—3_74
  18. Uidrou B., Stirnz S. Adaptivnaja obrabotka signalov: per. s angl. Moskwa: Radio i svjaz’, 1989. 440 p.
  19. Beregovenko G.Ja., Puhov G.E. Stupenchatye izobrazhenija i ih primenenie. Kiev: Nauk, dumka, 1983. 216 p.

Loading