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По вашему запросу найдено документов: 56278

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Review of methods of transformation, extraction and classification of EEG data for the identification of cognitive processes

Dedkov A.E., Andrikov B.A.

and approaches to their classification are analyzed.

Detection of Intrinsic Optical Signals in the Somatosensory Cortex of Neonatal Rats by Principal Components Analysis

Sintsov M., Suchkov D., Minlebaev M.

and requires other recording and analysis methods. We report here our assessment of the use of the principal

How to quantify sleepiness during an attempt to sleep?

Putilov A.A., Sveshnikov D.S., Yakunina E.B., Mankaeva O.V., Puchkova A.N., Shumov D.E., Gandina E.O., Taranov A.O., Ligun N.V., Donskaya O.G., Verevkin E.G., Dorokhov V.B.

frequency on the 2nd principal component of variation in the EEG spectrum (either sleepiness score or PC2

Peculiarities of modelling of the enterprise investment attractiveness in the conditions of multicollinearity of predictors

Yakupov N., Kvon G., Salahieva M., Kadochnikova E., Lelyukh A.

© Medwell Journals, 2017. The study presents an approach to assess the enterprise investment

Principal Directions of Digital Transformation of Higher Education System in Sustainable Education

Akhmetshin E., Barmuta K., Vasilev V., Okagbue H., Ijezie O.

approach, the article formulates the main directions of digital transformation of higher education system

A principal components analysis and functional annotation of differentially expressed genes in brain regions of gray rats selected for tame or aggressive behavior

Chadaeva I., Kozhemyakina R., Shikhevich S, Bogomolov A., Kondratyuk E., Oshchepkov D., Orlov Y.L., Markel A.L.

A principal components analysis and functional annotation of differentially expressed genes

Analysis of the velocity profile in Lake Shira in summer using principal component analysis

Володько, Ольга Станиславовна, Компаниец, Лидия Алексеевна, Гаврилова, Людмила Владимировна

greatly in depth as well as in time. The principal component method has been performed to analyze

Use of principal component analysis for identification of temporal and spatial patterns in the dynamics of ionospheric equatorial anomaly

Maslennikova Y., Bochkarev V., Voloskov D.

of the decomposition in principal components essentially depends on the method used for preprocessing the data

Generalized Embedding Regression: A Framework for Supervised Feature Extraction

Lu J., Lai Z., Wang H., Chen Y., Zhou J., Shen L.

. By utilizing this framework as a general platform, we design a novel supervised feature extraction approach

Face recognition system based on principal component analysis and support vector machine classification

Principal component analysis is a commonly used feature extraction technology in face recognition

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