Analysis of Data Transmission using one modified neural networks

Authors

  • Inna Kal’chuk Faculty of Information Technology and Mathematics  Lesya Ukrainka Volyn National University Lutsk, Ukraine
  • Serhii Laptiev Taras Shevchenko National University of Kyiv Faculty of information Technology Department of Cyber Security and Information Protection Kyiv, Ukraine
  • Tetiana Laptievа Taras Shevchenko National University of Kyiv Faculty of information Technology Department of Cyber Security and Information Protection Kyiv, Ukraine

DOI:

https://doi.org/10.33292/ijarlit.v3i2.49

Keywords:

data transmission, data flow, linear method of Fourier series, Neural network

Abstract

The traditional neural networks cannot provide modern mapping capability which is most important for analysis of data transmission nowadays. Therefore, Sigma-Pi-Sigma neural networks (SPSNNs) are good tool for this operation because of easy architecture. Application of integrated learning approach for neural networks, which uses sigma-pi-sigma neurons, helps us to complete their task for small period of time. It’s very necessary for neurons to find the solution of the problem. A final result of our results can be used in order to find the routes of “safety”, which we can indicate by position and state of cable lines or ties. For correct analysis and accurate results, we use pulse refectory method with using special device in order to get waveform, which introduce the connection problem. So, Sigma-Pi-Sigma neural network model is used for exact interpretation of altering probe signal. It is crucial that we also used rectangular methods of summation of Fourier series firstly. Therefore, it is main novelty of our investigation.

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Published

2022-04-02

How to Cite

Kal’chuk, I. ., Laptiev, S. ., & Laptievа T. (2022). Analysis of Data Transmission using one modified neural networks. International Journal Artificial Intelligent and Informatics, 3(2), 73–79. https://doi.org/10.33292/ijarlit.v3i2.49

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