Alexey Mekler

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Condition monitoring is an important and challenging task actual for many areas of industry, medicine and economics. Nowadays it is necessary to provide on-line monitoring of the complex systems status, e.g. the steel production, in order to avoid faults, breakdowns or wrong diagnostics. In the present paper a novel machine learning method for the automated(More)
Correlation dimension of reconstructed attractor (D(2)) is one of the specific values for human electroencephalogram (EEG). It makes it possible to evaluate variability of human brain functioning. There are some requirements, made for time series to be analyzed by Grassberger-Procaccia method, and EEG does not meet them perfectly. Also, realization of this(More)
Two artificial neural networks of different types were applied to gene expression profiles in glioblastoma, the most aggressive human brain tumor, and in normal brain tissue. The results of gene expression profiles classification are presented. First method, self organizing maps, gave good discrimination of profiles on the trained map. Another ANN,(More)
Two glioblastoma groups, which are distinguished from each other by expression level of 416 genes (p ≤ 0.05), were determined using a mathematical model of linear Boolean programming on the basis of gene expression data, obtained by microarray analysis of the glioblastomas and available in Gene Expression Omnibus (GEO) data base. The expression level of 15(More)
aInstitute of Human Brain, Russian Acad. Sci., Saint Petersburg, Russia; bCentral Astronomical Observatory at Pulkovo, Russian Acad. Sci., Saint Petersburg, Russia; cSaint Petersburg State Polytechnical University, Saint Petersburg, Russia; dSaint Petersburg State University, Saint Petersburg, Russia; eThe Institute of Molecular Biology and Genetics of(More)
In this paper the adaptive binary classifier is applied for the classification of the tensotremorogramm (TTG) time series. The idea is to reveal pathological states of human motor control system. Adaptive binary classifier being a new type of trained classifiers can be trained on the data for healthy subjects. Then the trained classifier can be used for the(More)
This paper deals with the Mie scattering kernels for multi-spectral data. The kernels may be represented in form of power series. Furthermore, the singular-value spectrum and the degree of ill-posedness in dependence on the refractive index of the particles are numerically approximated. A special hybrid regularization technique allows us to determine via(More)
MOTIVATION One of the important aspects of the data classification problem lies in making the most appropriate selection of features. The set of variables should be small and, at the same time, should provide reliable discrimination of the classes. The method for the discriminating power evaluation that enables a comparison between different sets of(More)
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