Competitive learning in neural networks
DOI:
https://doi.org/10.54309/IJICT.2020.3.3.011Ключевые слова:
Выбраны:competitive learning, neural networks, learning, perceptron, synaptic weightsАннотация
The article presents the basic concept of competitive learning in neural networks. Provides the main machine learning learning models and applications. The analysis of the advantages and disadvantages of these models is carried out. The geometric interpretation of competitive learning is presented in terms of mathematical formulas, as well as the behavior of neurons in this model. Neural systems are described as a powerful tool and driver in the field of modern Internet technologies, in data science and big (meta) data.
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Опубликован
2021-07-29
Как цитировать
Mukhanov S.B., Aldanazar A.A., Uatbayeva A.M., Alimbekov A.Ye., & Marat G.S. (2021). Competitive learning in neural networks. МЕЖДУНАРОДНЫЙ ЖУРНАЛ ИНФОРМАЦИОННЫХ И КОММУНИКАЦИОННЫХ ТЕХНОЛОГИЙ, 1(3). https://doi.org/10.54309/IJICT.2020.3.3.011
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Раздел
ИНТЕЛЛЕКТУАЛЬНЫЕ СИСТЕМЫ
Лицензия
https://creativecommons.org/licenses/by-nc-nd/3.0/deed.en