Competitive learning in neural networks
DOI:
https://doi.org/10.54309/IJICT.2020.3.3.011Keywords:
competitive learning, neural networks, learning, perceptron, synaptic weightsAbstract
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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Published
2021-07-29
How to Cite
Mukhanov S.B., Aldanazar A.A., Uatbayeva A.M., Alimbekov A.Ye., & Marat G.S. (2021). Competitive learning in neural networks. INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES, 1(3). https://doi.org/10.54309/IJICT.2020.3.3.011
Issue
Section
SMART SYSTEMS
License
https://creativecommons.org/licenses/by-nc-nd/3.0/deed.en