TY  - JOUR
T1  - Prospects for Multiple Reductions in Test Samples with a Multivariate,
Multicriteria, The Neural Network Statistical Analysis of Biometric Data
AU - Alibiyeva, Zhibek AU - Beketova, Gulzhanat AU - Mukapil, Kaiyrkhan AU - Ivanov, Alexander AU - Malygin, Alexander AU - Akhmetov, Berik AU - Zhumangalieva, Nazym 
JO  - Research Journal of Applied Sciences
VL  - 10
IS  - 12
SP  - 956
EP  - 967
PY  - 2015
DA  - 2001/08/19
SN  - 1815-932x
DO  - rjasci.2015.956.967
UR  - https://makhillpublications.co/view-article.php?doi=rjasci.2015.956.967
KW  - multivariate statistical processing
KW  -the capacity of statistical criteria
KW  -A set of statistical criteria
KW  -artificial neural networks
KW  -reduction
AB  - It is shown that the classical Chi-Square test has insufficient capacity for efficient processing of biometric data. It is shown that there is a possibility to increase the power of statistical processing through the use of several well-known statistical tests, through the neural network combining their private decisions. Contains tables of formulas promising statistical criteria that complement already used statistical tests. Considered the influence of quantization errors caused by the small amount of experience in the test sample. Proposed to raise the reliability of the estimates due to the digital smoothing of histograms with uniform quantization step. Shows the tables and nomograms to assess the reduction in the probability of errors of the first and second order transition to multivariate statistical analysis of biometric data.
ER  -