Entropy estimation of the position of the barrier dimension: Applicability nearsighted and farsighted iterative algorithms for processing high-dimensional data

• Published in: 2015 15th International Conference on Control, Automation and Systems (ICCAS) pp. 1329 - 1332
• Main Authors: Akhmetov, Berik, Ivanov, Alexander, Gilmutdinov, Anis, Ognev, Ivan, Mukapil, Kaiyrkhan
• Format: Conference Proceeding
• Language: English
• Published: Institute of Control, Robotics and Systems - ICROS 01-10-2015
• Subjects: address of neural networks; Biological system modeling; Correlation; Entropy; multidimensional entropy; neural networks
• ISSN: 2093-7121
• DOI: 10.1109/ICCAS.2015.7364844

It is shown that large neural networks allow solving tasks that cannot classical quadratic forms in linear algebra. Thus the assessment of output entropy of neural network converters biometrics code is possible. The assessment of high-dimensional entropy is based on the symmetrization of the problem of the correlation of biometric data. Entropy of low dimension and high-dimensional entropy are differently connected with equally correlated data. For low-dimensional transformations only short-sighted algorithms, which not capable to bypass local extrema of quality are effective. The algorithms constructed on the accounting of multidimensional entropy are far-sighted, they don't see local extrema.