title: ÐÑÐ¸Ð¼ÐµÐ½ÐµÐ½Ð¸Ðµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹ Ð´Ð»Ñ Ð´ÐµÐ¼Ð¾Ð´ÑÐ»ÑÑÐ¸Ð¸ Ð¼Ð½Ð¾Ð³Ð¾ÑÐ°ÑÑÐ¾ÑÐ½ÑÑ ÑÐ¸Ð³Ð½Ð°Ð»Ð¾Ð²
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: The application of neural networks for demodulating multifrequency signals
Creators: name: Ð¡ÐµÐ¼ÐµÐ½Ð¾Ð²Ð°, ÐÐ½Ð°ÑÑÐ°ÑÐ¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2021
Subjects: ÐÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
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description: The subject of the graduate qualification work is âThe application of neural net-works for demodulating multifrequency signalsâ. The given work is devoted to analysis of the application of neural networks for demodulating multifrequency signals when going through a channel with AWGN. The aim of the work is to evaluate the features of using neural networks for demodulating SEFDM signals. Four structures of fully connected neural networks for demodulating multi-frequency signals are implemented. Algorithms implemented with the help of a neural network were proposed: element-by-element reception, an algorithm that considers neighboring subcarriers and a modified full search. As a result of the work, a comparison of the computational complexity between all the proposed algorithms and the algorithm implemented earlier in another work was carried out. The training was conducted using the backpropagation. The computational complexity was calculated for 1 subcarrier. In the algorithm, considering the samples from neighboring subcarriers, it is not necessary to use more than four neighboring subcarriers, since the error probability remains unchanged, and the computational complexity increases. This result is reflected in this paper. We compared the modified full-search algorithm implemented in this paper, the algorithm considering neighboring subcarriers, with the reception algorithm based on full-search without considering neural networks, implemented in another paper. The results obtained indicate the energy gain of the demodulator using a neural network.