ARTIFICIAL NEURAL NETWORKS IN INFORMATION PROCESSING. PERCEPTRON (SENSES) AND THEIR PROPERTIES

Authors

  • Mamirkhojayev Muhammadamin Mavlonjonovich Students of the Fergana branch of TUIT named after Muhammad Al-Khwarizmi
  • Umaraliyev Jamshidbek Tokhtasinovich Students of the Fergana branch of TUIT named after Muhammad Al-Khwarizmi
  • Sotvoldiyeva Mohirakhon Bakhromjon qizi Students of the Fergana branch of TUIT named after Muhammad Al-Khwarizmi
  • Toychibaev Abbosjon Eraliyevich Students of the Fergana branch of TUIT named after Muhammad Al-Khwarizmi

Keywords:

Hopfield motorists, Hamming network, Bidirectional associative memory

Abstract

Hopfield neural network as automatic associative memory trained using Hebb method and projection method; Information on Hamming network-based heteroassociative memory and bidirectional associative memory is presented.

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Published

2022-07-06

How to Cite

Mamirkhojayev Muhammadamin Mavlonjonovich, Umaraliyev Jamshidbek Tokhtasinovich, Sotvoldiyeva Mohirakhon Bakhromjon qizi, & Toychibaev Abbosjon Eraliyevich. (2022). ARTIFICIAL NEURAL NETWORKS IN INFORMATION PROCESSING. PERCEPTRON (SENSES) AND THEIR PROPERTIES. European Scholar Journal, 3(7), 3-5. Retrieved from https://scholarzest.com/index.php/esj/article/view/2458

Issue

Vol. 3 No. 7 (2022): ESJ

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.