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Entropy Estimation of the Position of the Barrier Dimension
Berik Akhmetov,Alexander Ivanov,Anis Gilmutdinov,Ivan Ognev,Kaiyrkhan Mukapil 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
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.
The Family of Chi-Square Molecules Pearson
Bakhytzhan Akhmetov,Alexander Ivanov,Anis Gilmutdinov,Alexander Bezyaev,Yulia Funtikova 제어로봇시스템학회 2015 제어로봇시스템학회 국제학술대회 논문집 Vol.2015 No.10
It is shown that the Schrodinger equations are not the only equations that generate difficult splittable continuous-quantum conversion. Such equations are many and each of them can be used to create a continuous quantum processors or accelerators computing. As one example of a simple continuous-quantum equations is considered Chi-square transformation of Pearson. At small number of experiences distribution the chi-square has obviously expressed discrete character that is equivalent supervision of a range of conditions of some molecule. Conventionally such mathematical molecule can be called as Pearson"s molecule. There given the information already implemented, continuous quantum accelerator computing, designed for solving the inverse problem of neural network biometrics.