Method of pattern recognition based on the Boltzmann machine model
News of the Kabardin-Balkar scientific center of RAS, no. 6-2 (2015), pp. 54-60.

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This paper proposes an approach to solving the problem of pattern recognition based on neural networks using techniques of "deep learning". Various types of models, such as restricted Boltzmann machine, deep Boltzmann machine are studied. An algorithm for training the models in question is described. Computational experiments were conducted to determine the effectiveness of the approach developed. Advantages and disadvantages of the proposed method are identified.
Keywords: pattern recognition, artificial neural networks, Boltzmann machine, machine learning.
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L. A. Gladkov; N. V. Gladkova; A. N. Babynin; A. M. Ksalov. Method of pattern recognition based on the Boltzmann machine model. News of the Kabardin-Balkar scientific center of RAS, no. 6-2 (2015), pp. 54-60. http://geodesic.mathdoc.fr/item/IZKAB_2015_6-2_a7/

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