Open AccessAnalysis of Data Transmission using one modified neural networks
Author(s) -
I. V. Kal’chuk,
Serhii Laptiev,
Тетяна Лаптєва
Publication year - 2022
Publication title -
international journal artificial intelligent and informatics
Language(s) - English
Resource type - Journals
ISSN - 2622-626X
DOI - 10.33292/ijarlit.v3i2.49
Subject(s) - artificial neural network , sigma , computer science , waveform , novelty , algorithm , transmission (telecommunications) , artificial intelligence , telecommunications , physics , radar , philosophy , theology , quantum mechanics
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.