INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES

Competitive learning in neural networks

Authors

Mukhanov S.B. International Information Technology University
Aldanazar A.A. International Information Technology University
Uatbayeva A.M. International Information Technology University
Alimbekov A.Ye. International Information Technology University
Marat G.S. International Information Technology University

DOI:

https://doi.org/10.54309/IJICT.2020.3.3.011

Keywords:

competitive learning, neural networks, learning, perceptron, synaptic weights

Abstract

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

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Issue

Vol. 1 No. 3 (2020): INTERNATIONAL JOURNAL OF INFORMATION AND COMMUNICATION TECHNOLOGIES

Section

SMART SYSTEMS

License

https://creativecommons.org/licenses/by-nc-nd/3.0/deed.en

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