A simple way to assess the spectral lines informativity of a chi-square molecule in analyzing small samples of biometric data-Reference-Cited by-同舟云学术

A simple way to assess the spectral lines informativity of a chi-square molecule in analyzing small samples of biometric data

Published:2018 Issue:3 Volume:16 Page:404-409
ISSN:1451-4117
Container-title:Journal of Applied Engineering Science
language:en
Short-container-title:J Appl Eng Science

Author:

Ivanov Alexander,Gazin Alexei,Serikova Yulia

Publisher

Centre for Evaluation in Education and Science (CEON/CEES)

Subject

Mechanical Engineering,General Engineering,Safety, Risk, Reliability and Quality,Transportation,Renewable Energy, Sustainability and the Environment,Civil and Structural Engineering

Link

https://scindeks-clanci.ceon.rs/data/pdf/1451-4117/2018/1451-41171803404I.pdf

Reference18 articles.

1. Volchikhin, V.I., Ivanov, A.I., Funtikov, V.A. (2005). Fast learning algorithms for neural network mechanisms of biometric-cryptographic information protection. Publishing House of the Penza State University, Penza.;

2. Malygin, A.Yu., Volchikhin, V.I., Ivanov, A.I., Funtikov, V.A. (2006). Fast testing algorithms for neural network mechanisms of biometric-cryptographic information protection. Publishing House of the Penza State University, Penza.;

3. Yazov, Yu.K. (2012). Neural network protection of personal biometric data. Radio Engineering, Moscow.;

4. Federal Agency on Technical Regulating and Metrology. (2001). R 50.1.037-2002. Recommendations on standardization. Applied statistics. Rules for verifying the agreement between the experimental and the theoretical distributions. Part I. x2 type criteria.;

5. Serikova, N.I., Ivanov, A.I., Kachalin, S.V. (2014). Biometric stats: smoothing histograms based on small training sample. Scientific Journal of Science and Technology, vol. 3, no. 55, 146-150.;