Deep neural networks for channel estimation in underwater acoustic OFDM systems
Orthogonal frequency division multiplexing (OFDM) provides a promising modulation
technique for underwater acoustic (UWA) communication systems. It is indispensable to …
technique for underwater acoustic (UWA) communication systems. It is indispensable to …
Brain-inspired wireless communications: Where reservoir computing meets MIMO-OFDM
Reservoir computing (RC) is a class of neuromorphic computing approaches that deals
particularly well with time-series prediction tasks. It significantly reduces the training …
particularly well with time-series prediction tasks. It significantly reduces the training …
Method of integral estimation of channel state in the multiantenna radio communication systems
S Kalantayevska, H Pievtsov… - Восточно …, 2018 - irbis-nbuv.gov.ua
За результатами дослідження встановлено, що запропонований метод дозволяє
підвищити швидкість оцінювання стану каналу багатоантенних систем в середньому до …
підвищити швидкість оцінювання стану каналу багатоантенних систем в середньому до …
[HTML][HTML] A comparative study on parameters estimation of squirrel cage induction motors using neural networks with unmemorized training
Induction machines are often preferred in industrial applications at present. Therefore, it is
an important problem to know the electrical parameters of induction machines correctly …
an important problem to know the electrical parameters of induction machines correctly …
A systematic literature review on channel estimation in MIMO-OFDM system: Performance analysis and future direction
BMR Manasa, P Venugopal - Journal of Optical Communications, 2022 - degruyter.com
Abstract Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-
OFDM) is a familiar modern wireless broadband technology due to its resistance against …
OFDM) is a familiar modern wireless broadband technology due to its resistance against …
Signal detection scheme based on adaptive ensemble deep learning model
CB Ha, HK Song - IEEE Access, 2018 - ieeexplore.ieee.org
Accurate signal detection is one of the most important requirements of wireless
communication systems. The two most important processes of the signal detection are …
communication systems. The two most important processes of the signal detection are …
[HTML][HTML] Hospitalization status and gender recognition over the arboviral medical records using shallow and RNN-based deep models
In global health systems, clinicians have a challenging decision of a triage patient exposed
to arbovirus infections to determine they should be hospitalized. Diagnosing symptoms and …
to arbovirus infections to determine they should be hospitalized. Diagnosing symptoms and …
Enhanced efficiency BPSK demodulator based on one-dimensional convolutional neural network
M Zhang, Z Liu, L Li, H Wang - IEEE Access, 2018 - ieeexplore.ieee.org
In this paper, a novel binary phase shift keying demodulator based on 1-D convolutional
neural network (1-D CNN) is proposed. The utilization of neural networks to detect the …
neural network (1-D CNN) is proposed. The utilization of neural networks to detect the …
Deep learning for OFDM channel estimation in impulsive noise environments
X Li, Z Han, H Yu, L Yan, S Han - Wireless Personal Communications, 2022 - Springer
Impulsive noise suppression is essential in orthogonal frequency division multiplexing
(OFDM) systems, since impulsive noise may cause a serious decline in channel estimation …
(OFDM) systems, since impulsive noise may cause a serious decline in channel estimation …
A new training scheme for neural networks and application in non-linear channel equalization
S Panda, PK Mohapatra, SP Panigrahi - Applied soft computing, 2015 - Elsevier
This paper deals with the problem of equalization of channels in a digital communication
system. In the literature, artificial neural network (ANN) has been increasingly used for the …
system. In the literature, artificial neural network (ANN) has been increasingly used for the …