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Journal Radioengineering №2 for 2013 г.
Article in number:
Procedure of check adequacy of mathematical model signalformations means of detection of territorially distributed systems of protection
Authors:
N.V. Onufriev, A.V.Skridlevsky
Abstract:
At a development cycle of mathematical model signalformations a perspective sensor there is a problem check its adequacy with use of the empirical data received during natural experiment. It allows to estimate look-ahead properties of model and a possibility its application for calculation of parameters of a signal of all population plants of detection. The complex of methods an estimation of parameters presented in given paper is systematized and adapted for an estimation of adequacy of mathematical model signalformations sensors. The offered technique of an estimation adequacy of theoretical model is approved on an example a pointwise radio wave sensor and includes two basic procedures. The first consists in an estimation of errors an evaluation, that is quality check of process of modeling. The second procedure assumes the analysis residuals of modeling on presence of the helpful information and the regularities not considered by model. As a result of adequacy check it is possible to consider that the developed model of a pointwise radio wave sensor is adequate and can be applied to calculation of informational parameters from various biological plants as, at an estimation accuracy of modeling, relative errors of modeling do not exceed 5%, and residuals are independent, have the zero average, an identical (constant) variance and to submit to normal distribution.
Pages: 91-94
References
  1. Boks Dzh. Analiz vremennykh rjadov. Vyp. 1. Prognoz i upravlenie / pod red. Dzh. Boksa i G. Dzhenkinsa. M.: Mir. 1974. 406 s
  2. Blokhin V.G., Gludkin O.P. i dr. Sovremennyjj ehksperiment: Podgotovka, provedenie, analiz rezultatov. M.: Radio i svjaz. 1997. 232 s.
  3. Braverman EH.M., Muchnik I.B. Strukturnye metody obrabotki ehmpiricheskikh dannykh. M.: Nauka. 1983. 464 s.
  4. Drejjper N., Smit G. Prikladnojj regressionnyjj analiz. M.: Finansy i statistika. 1986. 365 s.
  5. Ventcel E. S. Teorija verojatnostejj: uchebnik dlja stud. vuzov. M.: Izdat. centr «Akademija». 2003. 576 s.